U.S. patent application number 15/756633 was filed with the patent office on 2019-10-17 for systems, methods, and apparatus for increasing bioreactor capacity using silica polymers.
The applicant listed for this patent is DRYLET, LLC. Invention is credited to M. Scott CONLEY, Mark MENENDEZ.
Application Number | 20190316070 15/756633 |
Document ID | / |
Family ID | 58188556 |
Filed Date | 2019-10-17 |
View All Diagrams
United States Patent
Application |
20190316070 |
Kind Code |
A1 |
CONLEY; M. Scott ; et
al. |
October 17, 2019 |
SYSTEMS, METHODS, AND APPARATUS FOR INCREASING BIOREACTOR CAPACITY
USING SILICA POLYMERS
Abstract
Disclosed herein are systems and methods that provide for
increased carrying capacity of bioreactors using silica polymers.
Disclosed is a method that includes supplying nutrients and silica
polymers containing microorganisms to a bioreactor to form a first
suspension and controlling temperature, pressure, and nutrient
conditions in the bioreactor to produce a second suspension with
increased carrying capacity as compared to a control bioreactor
containing microorganisms without the silica polymers.
Inventors: |
CONLEY; M. Scott; (Cypress,
TX) ; MENENDEZ; Mark; (Houston, TX) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
DRYLET, LLC |
Houston |
TX |
US |
|
|
Family ID: |
58188556 |
Appl. No.: |
15/756633 |
Filed: |
September 1, 2016 |
PCT Filed: |
September 1, 2016 |
PCT NO: |
PCT/US2016/050013 |
371 Date: |
March 1, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
62213094 |
Sep 1, 2015 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
C08G 77/02 20130101;
Y02W 10/15 20150501; C12M 21/12 20130101; C12M 25/16 20130101; C02F
3/348 20130101; C02F 3/107 20130101; C12N 1/38 20130101; C12N 11/14
20130101; C12M 41/40 20130101; C02F 3/108 20130101; C12M 41/12
20130101 |
International
Class: |
C12M 1/12 20060101
C12M001/12; C02F 3/10 20060101 C02F003/10; C12M 1/00 20060101
C12M001/00; C12N 1/38 20060101 C12N001/38; C12N 11/14 20060101
C12N011/14; C02F 3/34 20060101 C02F003/34; C12M 1/34 20060101
C12M001/34 |
Claims
1. A method for increasing microbial population, the method
comprising: supplying nutrients and silica polymers containing
microorganisms to a bioreactor to form a first suspension; and
controlling temperature, pressure, and nutrient conditions in the
bioreactor to produce a second suspension with increased carrying
capacity as compared to a control bioreactor containing
microorganisms without the silica polymers.
2. The method of claim 1, wherein the increased carrying capacity
of the bioreactor is at least 1.5 times carrying capacity of the
control bioreactor containing microorganisms without the silica
polymers.
3. The method of claim 1, wherein the microorganisms are
aerobic.
4. The method of claim 1, wherein the microorganisms are
anaerobic.
5. The method of claim 1, wherein the microorganisms produce a
biofuel.
6. The method of claim 5, wherein the biofuel is selected from the
group consisting of methanol, ethanol, and butanol.
7. The method of claim 1, the silica polymers are precipitated
silica granules having a porous structure and loaded with
microorganisms throughout the pores of the precipitated silica
granules.
8. A method for increasing the carrying capacity of a wastewater
treatment facility, the method comprising: introducing silica
polymers containing microorganisms to a bioreactor containing
wastewater to form a first suspension; maintaining the bioreactor
under conditions to produce a second suspension, wherein the second
suspension has at least two times more total suspended solids than
a control bioreactor without application of silica polymers;
separating, by a mechanical process, the second suspension to
produce a fraction containing suspended solids and a treated water
stream, wherein a portion of the fraction containing suspended
solids is recycled to the bioreactor.
9. The method of claim 8, wherein the silica polymers containing
microorganisms are introduced to a wastewater stream under aerating
conditions to form the first suspension.
10. The method of claim 8, wherein the silica polymers are
precipitated silica granules having a porous structure and loaded
with microorganisms throughout the pores of the precipitated silica
granules.
11. The method of claim 8, further comprising: adding a
flocculating agent to the second suspension.
12. The method of claim 8, wherein a portion of the fraction
containing suspended solids is supplied to an additional bioreactor
under anaerobic or anoxic conditions to produce digested
products.
13. The method of claim 12, further comprising: separating the
digested products to remove water from the digested products and
produce a filter cake.
14. A system for increasing the carrying capacity of a wastewater
treatment plant, the system comprising: an aeration basin
configured to mix wastewater and silica polymers containing
microorganisms to produce a first suspension; a bioreactor
configured to receive the first suspension and produce a second
suspension with at least two times more total suspended solids than
the wastewater stream; a first solid-liquid separator configured to
receive the second suspension from the bioreactor and produce a
first fraction containing suspended solids and a treated water
stream; and a second solid-liquid separator configured to receive
the first fraction containing suspended solids and produce a second
fraction containing suspended solids and a waste product stream
containing suspended solids, wherein the second fraction is
recycled to the bioreactor.
15. The system of claim 14, wherein the silica polymers are
precipitated silica granules having a porous structure and loaded
with microorganisms throughout the pores of the precipitated silica
granules.
16. The system of claim 14, further comprising: a third
solid-liquid separator configured to receive the waste product
stream and produce a water stream and a filter cake.
17. A system for increasing the carrying capacity of a wastewater
treatment plant, the system comprising: a bioreactor configured to
receive silica polymers containing microorganisms and wastewater
and produce a suspension with at least two times more total
suspended solids than the wastewater; a first solid-liquid
separator configured to receive the suspension from the bioreactor
and produce a first fraction containing suspended solids and a
treated water stream; and a second solid-liquid separator
configured to receive the first fraction containing suspended
solids and produce a second fraction containing suspended solids
and a waste product stream containing suspended solids, wherein the
second fraction containing suspended solids is recycled back to the
bioreactor.
18. The system of claim 17, further comprising: a third
solid-liquid separator configured to receive the waste product and
produce a water stream and a filter cake.
19. The system of claim 17, wherein the silica polymers are
precipitated silica granules having a porous structure and loaded
with microorganisms throughout the pores of the precipitated silica
granules.
20. A method for increasing microbial population, the method
comprising: supplying silica polymers and nutrients to a bioreactor
containing microbes to form a first suspension, wherein the silica
polymers provide a substrate for microbial growth; and controlling
reaction conditions in the bioreactor to produce a second
suspension with increased carrying capacity as compared to a
control bioreactor containing microorganisms without the silica
polymers.
Description
REFERENCE TO RELATED APPLICATION
[0001] This application is the National Stage entry of
International Application No. PCT/US2016/050013, filed Sep. 1,
2016, which claims the benefit of U.S. Provisional Application No.
62/213,094, filed Sep. 1, 2015, both of which are herein
incorporated by reference in their entireties.
TECHNICAL FIELD
[0002] The present disclosure relates in general to methods,
systems, and apparatus for increasing carrying capacity and
utilization of bioreactors using silica polymers, specifically
systems and methods for increasing organic mass conversion systems
using silica polymers. Also disclosed herein are systems and
methods for treatment of wastewater using silica polymers.
BACKGROUND
[0003] Bioreactions are utilized in wide range of industrial
processes, including but not limited to generation of biofuels,
treatment of water, food preparation and processing enterprises
such as in making alcoholic beverages, and manufacturing of
biological products, such as amino acids and recombinant
proteins.
[0004] Industrial bioreactions can be operated in a batch mode, a
continuous processing mode, or as a hybrid. For example, in the
manufacture of therapeutic biologic proteins, batch processing is
utilized to obtain stable clinical products at high titers.
Continuous bioprocessing is utilized for processes that require,
for example, an ongoing evolution of a mixed population of cells
that are capable of consuming large amounts of variable feedstock
all year around. Continuous bioprocessing is also used in instances
where there is production of products that negatively affect cell
growth or that are unstable, thus degrade under batch conditions.
Water, land, and energy resource management continue to be pressing
challenges facing our world, so process optimization of batch,
continuous, or hybrid bioprocessing modes is critical to conserving
resources and deriving maximum value from current processes
utilizing these resources. Process optimization can include
increasing operational efficiency, increasing carrying capacity of
the bioreaction system, and maximizing yields, while minimizing
consumption of raw materials and costs.
[0005] As an example, water management involves collection,
treatment, and recycling of both clean water and wastewater.
Wastewater treatment includes simple accumulation of wastewater
followed by discharge of untreated but screened wastewater streams
directly to bodies of water, wastewater treatment plants with
sophisticated treatment reactors. The products of the treatment
processes are primarily clean effluent and solids m the form of
sludge. Biological treatment of wastewater is accomplished by
growing bacteria m a continuous bioreaction mode under aerobic
conditions. Wastewater treatment models focus on global growth
rates without regard to the relative abundance of individual
species present. In fact, it is impossible to isolate and
accurately catalog all of the species present in a wastewater
aeration basin. Moreover, the wastewater industry provides the most
commonly encountered example of complex mixed culture interactions.
For several decades, others have attempted to reduce sludge in
wastewater systems by treating with products containing enzymatic
blends, liquid based microbial cultures or nutrient based microbial
cultures. These have been unsuccessful in reducing sludge.
Wastewater sludge consists mostly of water (typically 70-85%). So
land application and other potential technologies for energy
recovery require that fuel be spent to transport the sludge. Sludge
disposal means hauling vast quantities of water around our planet
every day. The most preferred waste management practice is not to
create the waste in the first place, thus the global objective is
to minimize solids production. In this way, sludge reduction
represents a movement towards better environmental stewardship and
sustainability. In addition, sludge reduction amounts to
significant water conservation, as the water content can be
returned to the groundwater supply rather than being evaporated
thereby contributing to impending water shortages.
[0006] Generally, methods involving bioprocessing steps are
relatively slow when compared with typical chemical processing
steps, as they are typically limited to moderate temperature and pH
ranges with relatively dilute streams. Thus, methodologies to
accelerate and increase carrying capacity in bioprocessing and
microbiologic treatments are needed to increase process efficiency
and to better utilize starting resources, effort, and time.
SUMMARY
[0007] Disclosed herein are systems and methods addressing the
shortcomings of the art, and may provide any number of additional
or alternative advantages. The system and methods described herein
provide increased carrying capacity for bioreactors.
[0008] Certain embodiments include a method for increasing
microbial population. The method includes the steps of supplying
nutrients and silica polymers containing microorganisms to a
bioreactor to form a first suspension; and controlling temperature,
pressure, and nutrient conditions in the bioreactor to produce a
second suspension with increased carrying capacity as compared to a
control bioreactor containing microorganisms without the silica
polymers.
[0009] In certain embodiments, the increased carrying capacity of
the bioreactor is at least 1.5 times carrying capacity of the
control bioreactor containing microorganisms without the silica
polymers.
[0010] The microorganisms can be aerobic. The microorganisms can be
anaerobic. The microorganisms produce a biofuel. The biofuel can be
selected from the group consisting of methanol, ethanol, and
butanol. In certain embodiments, the silica polymers are
precipitated silica granules having a porous structure and loaded
with microorganisms throughout the pores of the precipitated silica
granules.
[0011] Certain embodiments include a method for increasing the
carrying capacity of a wastewater treatment facility. The method
includes the steps of introducing silica polymers containing
microorganisms to a bioreactor containing wastewater to form a
first suspension; maintaining the bioreactor under conditions to
produce a second suspension, wherein the second suspension has at
least two times more total suspended solids than a control
bioreactor without application of silica polymers; separating, by a
mechanical process, the second suspension to produce a fraction
containing suspended solids and a treated water stream, wherein a
portion of the fraction containing suspended solids is recycled to
the bioreactor.
[0012] Another exemplary method includes the steps of introducing
wastewater and silica polymers containing microorganisms to a
bioreactor to form a first suspension; maintaining the bioreactor
under conditions to produce a second suspension, wherein the second
suspension has at least two times more total suspended solids than
the wastewater stream; separating, by a mechanical process, the
second suspension to produce a first fraction containing suspended
solids and a treated water stream; separating the first fraction
containing suspended solids into a second fraction containing
suspended solids and a waste product stream, wherein the second
fraction is recycled to the bioreactor. The method can also include
the step of adding a flocculating agent to the waste product stream
to produce a water stream and a filter cake.
[0013] In certain embodiments, the silica polymers containing
microorganisms are introduced to a wastewater stream under aerating
conditions to form the first suspension. In certain embodiments,
the silica polymers are precipitated silica granules having a
porous structure and loaded with microorganisms throughout the
pores of the precipitated silica granules.
[0014] An exemplary method for increasing microbial population
includes the steps of supplying silica polymers and nutrients to a
bioreactor containing microbes to form a first suspension, wherein
the silica polymers provide a substrate for microbial growth; and
controlling reaction conditions in the bioreactor to produce a
second suspension with increased carrying capacity as compared to a
control bioreactor containing microorganisms without the silica
polymers.
[0015] Certain embodiments include a system for increasing the
carrying capacity of a wastewater treatment plant. The system
includes an aeration basin configured to mix wastewater and silica
polymers containing microorganisms to produce a first suspension; a
bioreactor configured to receive the first suspension and produce a
second suspension with at least two times more total suspended
solids than the wastewater stream; a first solid-liquid separator
configured to receive the second suspension from the bioreactor and
produce a first fraction containing suspended solids and a treated
water stream; and a second solid-liquid separator configured to
receive the first fraction containing suspended solids and produce
a second fraction containing suspended solids and a waste product
stream containing suspended solids, wherein the second fraction is
recycled to the bioreactor. In certain embodiments, the silica
polymers are precipitated silica granules having a porous structure
and loaded with microorganisms throughout the pores of the
precipitated silica granules. The system can also include a third
solid liquid separator configured to receive the waste product
stream and produce a water stream and a filter cake.
[0016] Certain embodiments include a system for increasing the
carrying capacity of a wastewater treatment plant. The system
includes a bioreactor configured to receive silica polymers
containing microorganisms and wastewater and produce a suspension
with at least two times more total suspended solids than the
wastewater; a first solid-liquid separator configured to receive
the suspension from the bioreactor and produce a first fraction
containing suspended solids and a treated water stream; and a
second solid liquid separator configured to receive the first
fraction containing suspended solids and produce a second fraction
containing suspended solids and a waste product stream containing
suspended solids, wherein the second fraction containing suspended
solids is recycled back to the bioreactor.
[0017] The system can also include a third solid liquid separator
configured to receive the waste product and produce a water stream
and a filter cake. In certain embodiments, the silica polymers are
precipitated silica granules having a porous structure and loaded
with microorganisms throughout the pores of the precipitated silica
granules.
[0018] In certain embodiments, the concentration of mixed liquor
suspended solids in the second suspension is greater than 7,000
mg/L. In certain embodiments, the solids retention time of the
second suspension in the bioreactor is greater than twenty
days.
[0019] In certain embodiments, the system for increasing the
capacity of a wastewater treatment plant includes a bioreactor
configured to receive silica polymers containing microorganisms and
a wastewater stream and produce a suspension with at least twice
the microbial activity than the wastewater stream; a first
solid-liquid separator configured to receive the suspension from
the bioreactor and produce a first fraction containing suspended
solids and a second fraction containing a treated water stream. The
first fraction containing the suspended solids is divided into a
third fraction and a fourth fraction, wherein the third fraction is
recycled back to the bioreactor and the fourth fraction is
forwarded to a second bioreactor for digestion to produce digested
products. In certain embodiments, the system further includes a
second solid-liquid separator configured to receive the digested
products, and remove water from the digested products, and produce
a filter cake.
[0020] Numerous other aspects, features and benefits of the present
disclosure may be made apparent from the following detailed
description taken together with the drawing figures. The systems
can include less components, more components, or different
components depending on desired analysis goals. It should be
further understood that both the foregoing general description and
the following detailed description are exemplary and explanatory
and are intended to provide further explanation of the invention as
claimed.
BRIEF DESCRIPTION OF THE DRAWINGS
[0021] The present disclosure can be better understood by referring
to the following figures. The emphasis is placed upon illustrating
the principles of the disclosure.
[0022] FIG. 1 is the average BOD for the Atascocita WWTP facilities
exhibited an increasing concentration of BOD (mg/l) over the period
from August 2013 through March 2015, according to an
embodiment.
[0023] FIG. 2 illustrates a trend of decreasing water usage for
waste and suggests that water conservation is being achieved
through a combination of household utilities and changing water
consumption habits, according to an embodiment.
[0024] FIG. 3A is the historical trend (higher plotted line) and
the test period trend (lower plotted line) that show the number of
hauls of sludge per month, according to an embodiment.
[0025] FIG. 3B shows the trend for the bio-solids yield and the
performance for each month when the WAS rate was increased for a
period of time, according to an embodiment.
[0026] FIG. 4 is an Ashbook Press existing depreciation line and
projected depreciation line.
[0027] FIG. 5 is an Andritz Press existing depreciation line and
projected depreciation line.
[0028] FIG. 6 shows 5-year historical monthly average for power
(kWh) use from running the aeration blowers compared against the
monthly power consumption (kWh) during the testing period, in
accordance with an embodiment.
[0029] FIG. 7 shows the 5-year monthly average of total dry solids
plotted against the total dry solids produced for each month during
the testing period, in accordance with an embodiment.
[0030] FIG. 8 illustrates the dramatic and surprising change in
microbial growth rates in the aeration basins over an 8 month time
period, in accordance with an embodiment.
[0031] FIG. 9 illustrates that a new steady state has been
achieved, m accordance with an embodiment.
[0032] FIG. 10 is a graph of the mass under aeration shows the
increasing trend of the total mass during the testing period, in
accordance with an embodiment.
[0033] FIGS. 11A-D indicate that all of the key performance
indicators showed a steady and dramatic increase during the product
test period, in accordance with an embodiment.
[0034] FIG. 12 shows the analytical results of the effluent during
a testing period, in accordance with an embodiment.
[0035] FIG. 13 is an image of superior quality sludge, in
accordance with an embodiment.
[0036] FIG. 14 is a graph of the TSS trend during a test period, in
accordance with an embodiment.
[0037] FIG. 15 is a batch reactor vessel in accordance with an
embodiment.
[0038] FIG. 16 is a graphical representation of the growth kinetics
of microorganisms growing under certain conditions, in accordance
with an embodiment.
[0039] FIG. 17 is a graphical representation of the mass to gas
percentage increase (about 9% more) under a second set of growth
conditions as compared to that under a first set of growth
conditions, in accordance with an embodiment.
[0040] FIG. 18 is a graphical representation of the rate of sugar
consumption under two growth conditions, in accordance with an
embodiment.
[0041] FIG. 19 is a graphical representation of the logarithmic
rate of sugar consumption under two growth conditions, in
accordance with an embodiment.
[0042] FIG. 20 is a graphical representation of the growth kinetics
of microorganisms growing in two conditions, in accordance with an
embodiment.
[0043] FIG. 21 is a graphical representation of the mass to gas
percentage increase under a second set of growth conditions as
compared to that under a control set of growth conditions, in
accordance with an embodiment.
[0044] FIG. 22 is a graphical representation of the rate of sugar
consumption under two growth conditions, in accordance with an
embodiment.
[0045] FIG. 23 is a graphical representation of the logarithmic
rate of sugar consumption under two growth conditions, in
accordance with an embodiment.
[0046] FIG. 24 is a graphical representation of the growth kinetics
of microorganisms growing under two growth conditions, in
accordance with an embodiment.
[0047] FIG. 25 is a graphical representation of the mass to gas
percentage increase under a second set of growth conditions as
compared to that under a control growth conditions, in accordance
with an embodiment.
[0048] FIG. 26 is a graphical representation of the rate of sugar
consumption under two growth conditions, in accordance with an
embodiment.
[0049] FIG. 27 is a graphical representation of the logarithmic
rate of sugar consumption under two growth conditions, in
accordance with an embodiment.
[0050] FIG. 28 is a graphical representation of the mannitol
production under two growth conditions, in accordance with an
embodiment.
[0051] FIG. 29 is a graphical representation of the ethanol
production under two growth conditions, in accordance with an
embodiment.
[0052] FIG. 30 is a graphical representation of the sugar uptake
under two growth conditions, in accordance with an embodiment.
[0053] FIG. 31 is a graphical representation of the growth kinetics
of microorganisms growing under two conditions, in accordance with
an embodiment.
[0054] FIG. 32 is a graphical representation of the mass to gas
percentage increase under a second set of growth conditions as
compared to that under control growth conditions, in accordance
with an embodiment.
[0055] FIG. 33 is a graphical representation of the rate of sugar
consumption under two growth conditions, in accordance with an
embodiment.
[0056] FIG. 34 is a graphical representation of the logarithmic
rate of sugar uptake under two growth conditions, in accordance
with an embodiment.
[0057] FIG. 35 is a diagrammatic representation of the experimental
set-up designed to study the amount of gasses produced by the
anaerobic systems, in accordance with an embodiment.
[0058] FIG. 36 is a graphical representation of the average mass
rate of gasses produced under the two growth conditions described
in Example 2a, in accordance with an embodiment.
[0059] FIG. 37 is a graphical representation of the average mass
rate of gasses produced under the two growth conditions described
in Example 2b, in accordance with an embodiment.
[0060] FIG. 38 is a graphical representation of the average mass
rate of gasses produced under the two growth conditions described
in Example 2c, in accordance with an embodiment.
[0061] FIG. 39 is a graphical representation of the average mass
rate of gasses produced under the two growth conditions described
in Example 2d, in accordance with an embodiment.
[0062] FIG. 40 is a graphical representation of the total gas
produced per unit vol. of starting culture when there was lower
amount food in the system (15 g/l), in accordance with an
embodiment.
[0063] FIG. 41 is a graphical representation of the rate of gas
(cc/hr) generated under three conditions (Reactors 1, 3, and 5)
normalized to the amount of unit volume in the starting culture as
measured by milliliters (ml), in accordance with an embodiment.
[0064] FIG. 42 is a graphical representation of butyric acid
production per unit volume of starting culture when there was lower
amount food in the system (15 g/l), in accordance with an
embodiment.
[0065] FIG. 43 is a graphical representation of the rate of butyric
acid production per unit volume of starting culture when there was
lower amount food in the system (15 g/l), in accordance with an
embodiment.
[0066] FIG. 44 is a graphical representation of the total gas
produced per unit vol. of starting culture when there was lower
amount food in the system (15 g/l) but the amount of silica present
was increased to 30 g, in accordance with an embodiment.
[0067] FIG. 45 is a graphical representation of the rate of gas
(cc/hr) generated under three conditions (Reactors 2, 4, and 5 in
Table 26) normalized to the amount of unit volume in the starting
culture as measured by milliliters (ml), in accordance with an
embodiment.
[0068] FIG. 46 is a graphical representation of butyric acid
production per unit volume of starting culture when there was lower
amount food in the system (15 g/l) but the amount of silica present
was increased to 30 g, in accordance with an embodiment.
[0069] FIG. 47 is a graphical representation of the rate of butyric
acid production per unit volume of starting culture when there was
lower amount food in the system (15 g/l) but the amount of silica
present was increased to 30 g, in accordance with an
embodiment.
[0070] FIG. 48 is a graphical representation of the total gas
produced per unit vol. of starting culture when there was larger
amount food in the system (30 g/l), in accordance with an
embodiment.
[0071] FIG. 49 is a graphical representation of the rate of gas
(cc/hr) generated under three conditions (Reactors 6, 8, and 10 in
Table 27) normalized to the amount of unit volume in the starting
culture as measured by milliliters (ml), in accordance with an
embodiment.
[0072] FIG. 50 is a graphical representation of butyric acid
production per unit volume of starting culture when there was
larger amount food in the system (30 g/l), in accordance with an
embodiment.
[0073] FIG. 51 is a graphical representation of the rate of butyric
acid production per unit volume of starting culture, in accordance
with an embodiment.
[0074] FIG. 52 is a graphical representation of the total gas
produced per unit vol. of starting culture when there was larger
amount food in the system (30 g/l) and the amount of silica present
was increased to 30 g, in accordance with an embodiment.
[0075] FIG. 53 is a graphical representation of the rate of gas
(cc/hr) generated under three conditions (Reactors 7, 9, and 10 in
Table 27) normalized to the amount of unit volume in the starting
culture as measured by milliliters (ml), in accordance with an
embodiment.
[0076] FIG. 54 is a graphical representation of butyric acid
production per unit volume of starting culture when there was
larger amount food in the system (30 g/l) and the amount of silica
present was increased to 30 g, in accordance with an
embodiment.
[0077] FIG. 55 is a graphical representation of the rate of butyric
acid production per unit volume of starting culture, in accordance
with an embodiment.
DETAILED DESCRIPTION
[0078] Reference will now be made to the exemplary embodiments
illustrated in the drawings, and specific language will be used
here to describe the same. It will nevertheless be understood that
no limitation of the scope of the invention is thereby intended.
Alterations and further modifications of the inventive features
illustrated here, and additional applications of the principles of
the inventions as illustrated here, which would occur to one
skilled in the relevant art and having possession of this
disclosure, are to be considered within the scope of the invention.
The present disclosure can be better understood by referring to the
attached figures. The components in the figures are not necessarily
to scale. The emphasis is instead placed upon illustrating the
principles of the disclosure. In the figures, reference numerals
designate corresponding parts throughout the different views.
[0079] As used here, the following terms may have the following
definitions:
[0080] "Bioreactor," as used herein is a system containing
microorganisms, in which materials are converted by the
microorganisms, or products produced by the microorganisms, or in
which increased cell population is achieved. Bioreactors used
herein can be one or more of batch reactors, fed-batch reactors,
semi-continuous reactors, continuous stirred-tank reactors,
continuous flow stirred-tank reactors, and plug-flow reactors,
singularly or in series; ebullized-bed (i.e., "bubbling and
boiling") reactors; and fluidized-bed reactors. In certain
embodiments, the bioreactor can be an aeration basin. In certain
embodiments, the bioreactor can be one or more of a trickling bed
reactor, percolating reactors, fluidized reactor, plug-flow
reactor, counter-current reactors, sequential batch reactors
("SBR"), and rotating biological contactors.
[0081] "Wastewater treatment," as used herein, refers to a process
that converts water that is contaminated water or unsuitable for
consumption by plants or animals into an effluent that can be
reused for another purpose or returned to the water cycle.
[0082] "Silica polymer," as used herein, refers to precipitated
silica granules having a porous structure, super absorbent silica
polymers, crystalline silica, fused quartz, fumed silica, silica
gels, aerogels, or colloidal silica. In certain embodiments, the
silica polymer is precipitated silica granules having a porous
structure. For example, suitable precipitated silica granules
include those formulated as DryLet.RTM. products, such as
DryLet.RTM. LIFT, DryLet.RTM. Aqua Assist, and DryLet.RTM. FOG.
[0083] "Microorganisms," as used herein, refers to include
bacteria, viruses, mycoplasma, fungi, and protozoa. In certain
embodiments, the microorganisms contained in the silica polymers
are bacteria. The microorganisms contained in the silica polymers
can be a blend of one or more species or genera of bacteria. The
microorganism(s) can be selected of one skilled in the art based on
the intended use, the available feed sources, and the desired
operating conditions for the bioreactor. For example, in a WWTP,
these microorganisms do the work of stabilization of organic waste
through the production of biomass sludge. Activated sludge
treatment relies on native microorganisms present in human flora
and in storm water run-off to convert organic material in the
influent into new biomass, and old solids or dead biomass in the
return activated sludge ("RAS") into new microorganisms.
[0084] "Carrying capacity" of the suspension or a medium, as used
herein, refers to the maximum population that a particular
bioreaction system can support. In a continuous bioreaction system
(a biostat or chemostat), such as a WWTP, it is measured as total
suspended solids ("TSS"), mixed liquor suspended solids ("MLSS"),
or volatile suspended solids ("VSS") in units of measure of
milligrams per liter. The increased carrying capacity can also be
measured by the increased rate of consumption of glucose or other
sugars. In a batch system that is not continuously fed with either
microbes or food, the carrying capacity can be measured by the peak
population density of microbes or alternatively from measuring the
rate of growth of the microbes and the rate of consumption of
food.
[0085] One embodiment of the invention is a composition for
delivering microorganisms in a dry mode that contains silica
polymers having a porous structure, and microorganisms loaded onto
the silica polymer. In another embodiment, microorganisms and the
nutrients required for their optimal growth are delivered to a
bioreactor with the independent addition of a silica polymer. In
another embodiment, the delivery of the microorganisms and
nutrients can be achieved by loading the silica polymer with the
microorganisms and nutrients to a desired capacity, then applying
the loaded product to the bioreactor.
[0086] Embodiments of the invention include utilization of the
silica polymer loaded with microorganisms in bioreactions occurring
in batch reactors. Embodiments of the invention include utilization
of the silica polymer loaded with microorganisms in bioreactions
occurring in continuous reactors. Embodiments of the invention
include utilization of the silica polymer loaded with
microorganisms in bioreactions carried out in a hybrid of batch and
continuous modes. The bioreactions in the batch, continuous, or
hybrid modes can be carried out under aerobic or anaerobic
conditions depending on the bioreaction and the organism(s)
involved. Embodiments of the invention include utilization of the
silica polymer loaded with microorganisms to produce biofuels,
including but not limited to methanol, ethanol, or butanol.
Embodiments of the invention include utilization of the silica
polymer loaded with microorganisms to produce biogas. Embodiments
of the invention include utilization of the silica polymer loaded
with microorganisms to produce amino acids. Embodiments of the
invention include utilization of the silica polymer loaded with
microorganisms to produce therapeutically important peptides.
[0087] Provided herein are certain embodiments of methods for
increasing the carrying capacity of a bioreactor, and also
increasing the sustainable utilization of bioreactors using silica
polymers. In an exemplary embodiment, the method includes providing
a nutrient stream to a bioreactor, and introducing silica polymers
containing microorganisms to the bioreactor to form a first
suspension. In certain embodiments, the silica polymers containing
microorganisms are introduced to the nutrient stream under aerating
conditions to form the first suspension before entering the
bioreactor. In certain embodiments, the silica polymers are
precipitated silica granules having a porous structure and loaded
with microorganisms throughout the pores of the precipitated silica
granules. The bioreactor containing the first suspension is
operated under conditions to form a second suspension that has at
least two times more TSS than the first suspension. The second
suspension is then subject to a first separation process to produce
a first fraction containing suspended solids and the residual
liquid stream. The first fraction containing suspended solids is
subject to a second separation process to produce a recycle stream
back to the bioreactor and a waste product stream containing
suspended solids.
[0088] An embodiment includes DryLet.RTM. LIFT--a proprietary
delivery platform for enhanced microbial activity in WWTPs. It is a
dry-to-the-touch product that consists of a mixed culture of
beneficial microbes immobilized on an inert stratum. For example,
the native, non-pathogenic consortium of microbial species is ideal
for wastewater application. The microbial species present are not
genetically modified strains and belong to the class of Group 1
microorganisms according to the World Health Organization
("WHO")--microorganisms that are unlikely to cause human disease or
animal disease. This product produces blooms of beneficial bacteria
when placed into an aqueous environment containing a food source in
the form of biomass or dead cells.
[0089] A wastewater treatment plant is a continuous process that is
modeled as a chemostat. The WWTP must grow as many bacteria as it
wastes out, or washout will occur and the WWTP will be emptied of
its beneficial bacteria. Growth rates of single species in batch
are well understood and are described by Michaelis-Menten kinetics.
The bacteria will grow exponentially until the food source is
depleted and crowding occurs. Exponential growth is log-linear and
corresponds to a very short doubling time for the population.
Substrate uptake, or food consumption, is extremely rapid during
exponential growth. When the carrying capacity is reached, rapid
growth stops and the microorganisms enter a stationary phase. In
the stationary phase, the number of bacteria that are "born" equals
the number of bacteria that "die" so that the overall population
remains unchanged. In this phase, substrate uptake corresponds to a
"maintenance" requirement. The population must consume some food
just to stay alive. The bacterial population in a WWTP consists
primarily of microorganisms in the stationary phase. Eventually,
when substrate has been depleted, the population begins to decline
by "endogenous decay." Endogenous decay involves cell lysis and the
conversion of dead cell mass into food for other viable bacteria.
Endogenous decay depletes the population after all the food is
gone. The viable bacteria consume the contents of dead cells in a
cannibalistic fashion. Activated sludge treatment capitalizes on
this predation by recycling activated sludge back to become food
for younger microorganisms in the aeration basin.
[0090] Precipitated silica granules are highly porous and contain a
huge surface area within their volume and on the surface. For
example, the DryLet.RTM. LIFT product has approximately about
700,000 square feet per pound in surface area. As with any
catalyst, the surface area provides a matrix upon which a reaction
can be greatly accelerated. The precipitated silica granules are
also a super absorbent polymer that is capable of drawing in
organic nutrients to be used as building blocks for new bacterial
cells and to sustain cellular functions. As the microorganisms
reach exponential growth phase, they experience crowding effects
within the silica polymers and begin to populate the surrounding
medium.
[0091] Provided herein are certain embodiments of methods for
increasing the carrying capacity of a WWTP. In an exemplary
embodiment, the method includes the steps of introducing wastewater
and silica polymers containing microorganisms to a bioreactor to
form a first suspension; maintaining the bioreactor under
conditions to produce a second suspension, wherein the second
suspension has at least two times more total suspended solids than
the wastewater stream; separating, by a mechanical process, the
second suspension to produce a first fraction containing suspended
solids and a treated water stream; separating the first fraction
containing suspended solids into a second fraction containing
suspended solids and a waste product stream, wherein the second
fraction is recycled to the bioreactor. The method can also include
the step of adding a flocculating agent to the waste product stream
to produce a water stream and a filter cake.
[0092] In certain embodiments, the silica polymers containing
microorganisms are introduced to a wastewater stream under aerating
conditions to form the first suspension. In certain embodiments,
the silica polymers are precipitated silica granules having a
porous structure and loaded with microorganisms throughout the
pores of the precipitated silica granules.
[0093] The following key performance indicators are commonly used
in the WWTP industry, and have been used here to evaluate the
performance of the systems: amount of mixed liquor suspended solids
(MLSS), wasted activated sludge (WAS), Volatile Suspended Solids
(VSS), Total Suspended Solids (TSS), Recycle Ratio, Return
Activated Sludge (RAS), Biological Oxygen Demand (BOD), Dissolved
Oxygen (DO), and Sludge Blanket Height. Key performance indicators
in WWTP focus on suspended and settled solids. One such indicator
is the Solids Retention Time (SRT) because it is undesirable to
remove active microorganisms or those in the log phase. If the
Solids Retention Time is too long, multicellular organisms or
undesired microorganisms become entrenched and affect the system
adversely. In cold climates that are not suited for microbial
activity, biological treatment is even called "secondary
treatment." In these WWTPs much of the organic waste is never
converted to biomass, it is just settled out in primary
clarifiers.
[0094] In certain embodiments, the yield measured as unit mass of
waste product produced per unit mass of organic loading is less
than about 40%. In certain embodiments, the yield measured as unit
mass of waste product produced per unit mass of organic loading is
less than about 30%. In certain embodiments, the yield measured as
unit mass of waste product produced per unit mass of organic
loading is less than about 20%. Lower yield represents minimization
or reduction of biosolids for wastewater treatment.
[0095] In certain embodiments, the concentration of MLSS in the
second suspension is greater than 7,000 mg/L. In certain
embodiments, the concentration of MLSS in the second suspension is
greater than 8,000 mg/L. In certain embodiments, the concentration
of MLSS in the second suspension is greater than 9,000 mg/L. In
certain embodiments, the concentration of MLSS in the second
suspension is greater than 10,000 mg/L. In certain embodiments, the
concentration of MLSS in the second suspension is greater than
11,000 mg/L. In certain embodiments, the concentration of MLSS in
the second suspension is greater than 12,000 mg/L. Increasing MLSS
is an important measure for determining the load to a solid liquid
separator like a clarifier. Depending on the settling
characteristics of the MLSS, which may differ from system to
system, it is vital to determine the upper boundary of solids
concentration or MLSS being fed to a clarifier or other type of
solid liquid separator. The solid liquid separator surface area and
the mass rate of suspended solids being introduced into a clarifier
allow for the determination of the mass flux, which is a process
design parameter for determining the operational size of the
clarifier. A higher MLSS also has the added benefit of a higher
VSS, which intrinsically has higher microbial activity that
benefits the WWTP operations.
[0096] In certain embodiments, the solids retention time of the
second suspension in the bioreactor is greater than twenty days. In
certain embodiments, the solids retention time of the second
suspension in the bioreactor is greater than thirty days. In
certain embodiments, the solids retention time of the second
suspension in the bioreactor is greater than forty days. In certain
embodiments, the solids retention time of the second suspension in
the bioreactor is greater than forty-five days. In certain
embodiments, the solids retention time of the second suspension in
the bioreactor is greater than fifty days. In certain embodiments,
the solids retention time of the second suspension in the
bioreactor is greater than sixty days.
[0097] In certain embodiments, the methods described herein include
adding a flocculating agent to the waste product stream to produce
a water stream and a filter cake. In certain embodiments, the
flocculating agent is one or more of an ionic polymer, a non-ionic
polymer, and combinations thereof. In certain embodiments, the
ionic polymer is a cationic polymer. In certain embodiments, the
ionic polymer is an anionic polymer.
[0098] In certain embodiments, the reduction of the amount of
sludge produced at the WWTP is at least about 40%, when compared to
systems that do not employ the silica polymers loaded with
microorganisms. In certain embodiments, the reduction of the amount
of sludge is at least about 30%. In certain embodiments, the
reduction of the amount of sludge is at least about 25%, when
compared to systems that do not employ the silica polymers loaded
with microorganisms. In certain embodiments, the reduction of the
amount of sludge is at least about 20% when compared to systems
that do not employ the silica polymers loaded with microorganisms.
In certain embodiments, the reduction of the amount of sludge is at
least about 15%.
[0099] The economic benefit for sludge reduction including savings
of financial, time, and personnel resources associated with sludge
disposal, consumption of flocculating agents such as polymers,
equipment life, and equipment maintenance costs. There are other
potential value drivers that may lead to more savings per year and
affect the WWTP operational costs, such examples without
limitations include lower oxygen demand, higher blower efficiency,
decreased qualitative and quantitative use of chemicals for
sanitation, and extended WWTP life.
[0100] In certain embodiments, the bioreaction system utilizes
flocculating agents, which can be one or more of an ionic polymer,
a non-ionic polymer, and combinations thereof. Examples include
aluminum chloride, ferric chloride and alum. In certain
embodiments, the ionic polymer is a cationic polymer, such as
agents based on copolymers of AETAC (N,N-Dimethylaminoethyl
Acrylate Methyl Chloride Quaternary) or METAC
(N,N-Dimethylaminoethyl Methacrylate Methyl Chloride Quaternary)
and acrylamide. These products can perform a dual function by both
coagulating with their positive ionic charge and flocculating with
their high molecular weight. In certain embodiments, the ionic
polymer is an anionic polymer, such as agents based on copolymers
of acrylamide and acrylic acid, anionic flocculants possess a
negative ionic charge and work by binding with residual cationic
charges on coagulants adsorbed to coagulated colloids. In certain
embodiments, there is at least about 45% reduction in consumption
of flocculating agents, when compared to systems that do not employ
the silica polymers loaded with microorganisms. In certain
embodiments, there is at least about 40% reduction in consumption
of flocculating agents, when compared to systems that do not employ
the silica polymers loaded with microorganisms. In certain
embodiments, there is at least about 35% reduction in consumption
of flocculating agents, when compared to systems that do not employ
the silica polymers loaded with microorganisms. In certain
embodiments, there is at least about 30% reduction in consumption
of flocculating agents, when compared to systems that do not employ
the silica polymers loaded with microorganisms. In certain
embodiments, there is at least about 25% reduction in consumption
of flocculating agents, when compared to systems that do not employ
the silica polymers loaded with microorganisms. In certain
embodiments, there is at least about 20% reduction in consumption
of flocculating agents, when compared to systems that do not employ
the silica polymers loaded with microorganisms.
[0101] Also provided herein are embodiments of systems for
increasing the carrying capacity of a WWTP. An exemplary system
includes a system for increasing the carrying capacity of a
wastewater treatment plant. The system includes an aeration basin
configured to mix wastewater and silica polymers containing
microorganisms to produce a first suspension; a bioreactor
configured to receive the first suspension and produce a second
suspension with at least two times more total suspended solids than
the wastewater stream; a first solid-liquid separator configured to
receive the second suspension from the bioreactor and produce a
first fraction containing suspended solids and a treated water
stream; and a second solid-liquid separator configured to receive
the first fraction containing suspended solids and produce a second
fraction containing suspended solids and a waste product stream
containing suspended solids, wherein the second fraction is
recycled to the bioreactor. In certain embodiments, the silica
polymers are precipitated silica granules having a porous structure
and loaded with microorganisms throughout the pores of the
precipitated silica granules. The system can also include a third
solid liquid separator configured to receive the waste product
stream and produce a water stream and a filter cake.
[0102] Another example includes a bioreactor configured to receive
silica polymers containing microorganisms and wastewater and
produce a suspension with at least two times more total suspended
solids than the wastewater; a first solid-liquid separator
configured to receive the suspension from the bioreactor and
produce a first fraction containing suspended solids and a treated
water stream; and a second solid liquid separator configured to
receive the first fraction containing suspended solids and produce
a second fraction containing suspended solids and a waste product
stream containing suspended solids, wherein the second fraction
containing suspended solids is recycled back to the bioreactor. The
system can also include a third solid liquid separator configured
to receive the waste product and produce a water stream and a
filter cake. In certain embodiments, the silica polymers are
precipitated silica granules having a porous structure and loaded
with microorganisms throughout the pores of the precipitated silica
granules. In certain embodiments, the concentration of mixed liquor
suspended solids in the second suspension is greater than 7,000
mg/L. In certain embodiments, the solids retention time of the
second suspension in the bioreactor is greater than twenty
days.
[0103] In certain embodiments, the system for increasing the
capacity of a wastewater treatment plant includes a bioreactor
configured to receive silica polymers containing microorganisms and
a wastewater stream and produce a suspension with at least twice
the microbial activity than the wastewater stream; a first
solid-liquid separator configured to receive the suspension from
the bioreactor and produce a first fraction containing suspended
solids and a second fraction containing a treated water stream. The
first fraction containing the suspended solids is divided into a
third fraction and a fourth fraction, wherein the third fraction is
recycled back to the bioreactor and the fourth fraction is
forwarded to a second bioreactor for digestion to produce digested
products. In certain embodiments, the system further includes a
second solid-liquid separator configured to receive the digested
products, and remove water from the digested products, and produce
a filter cake.
[0104] Certain key performance indicators from systems that employ
various wastewater treatment systems are shown below in Table IA.
These values are from a WWTP operator manual, for example provided
at
http://dca.kv.gov/certification/test%20preparation%20documents/l;vaste'Vv-
ater'7c.20treatment%20plant%20operator%20certification%20manual%20-%20revi-
sed%20092811.pdf. Also included in Table 1B is a comparison of
these performance indicators of an exemplary system employing the
silica polymers loaded with the microorganisms.
TABLE-US-00001 TABLE 1A Typical Design Parameters for Activated
Sludge Processes Organic Return F/M lbs. Loading Detention Flow to
Process SRT BOD/lb. (lbs.BOD/ MLSS Time Plant Flow Modification
(DAYS) MLVSS/day 1000 ft.sup.3) (mg/L) (hours) Ratio Conventional
5-15 0.2-0.5 20-40 1000-3000 4-8 0.25-0.75 Complete Mix 1-15
0.2-1.0 50-120 1000-6500 3-5 0.25-1.0 Step Feed 3-15 02.-0.5 40-60
1500-3500 3-5 0.25-0.75 Modified Aeration 0.2-0.5 1.5-5.0 75-150
200-1000 1.5-3.0 0.05-0.25 Contact 5-15 0.2-0.6 60-75 1000-3000
0.5-1.0 0.5-1.5 Stabilization 4000-9000 3-6 Extended Aeration 20-30
0.05-0.15 12.5-15 2000-6000 18-36 0.5-1.5 Oxidation Ditch 10-30
0.05-0.15 12.5-15 2000-6000 18-36 0.75-1.5 High Purity 3-10
0.25-1.0 100-200 3000-8000 1-3 0.25-0.5 Oxygen Kraus Process 5-15
0.3-0.8 40-100 2000-3000 4-8 0.5-1.0
TABLE-US-00002 TABLE 1B Typical Design Parameters for Activated
Sludge Processes Return F/M lbs. Organic Detention Flow to Process
SRT BOD/lb. Loading MLSS Time Plant Flow Modification (DAYS)
MLVSS/day (lbs.BOD/1000 ft.sup.3) (mg/L) (hours) Ratio DryLet .RTM.
30-50 0.5-0.05 20-200 7,000-11,000 4-17 0.5-2.0 process
[0105] Most WWTPs are designed to have a recycle ratio between 50
and 150% of the influent flow rate. The typical range for dissolved
oxygen, which is the amount of oxygen that is present in the water,
measured in milligrams per liter, and is usually between 2 and 3.5
mg/l in the aeration basin. In most systems in the art, control is
achieved by keeping a constant MLSS or a constant solids retention
time. The MLSS typically ranges between 2500 and 3500 mg/l. Solids
retention time will usually range between 10 and 20 days. The
operator will change the wasting rate, which is a fraction of the
clarifier underflow to keep a steady-state population, measured as
MLSS in the basins. The operator will keep a constant sludge
blanket in the clarifiers by changing the RAS or recycle ratio
raising the return activated sludge flow rate as blanket height
climbs and lowering return activated sludge flow rate if blankets
begin to fall.
[0106] Most of the VSS into the WWTP (80-90%) are organic
foodstuffs like carbohydrates, lipids, and proteins. A small
fraction of the VSS coming into the WWTP is composed of
nonbiodegradable VSS ("nbVSS"). About 10% of the TSS into the WWTP
are composed of inorganic material like metals and silt. Neither
the nbVSS nor the inert inorganics will be consumed by biological
activity. These solids are not the target of activated sludge
treatment. The non-biodegradable solids will simply pass through
the WWTP with the vast majority exiting in the generated sludge and
a very small amount remaining suspended and exiting at the outfall
per limits set by the EPA. Some fraction, f.sub.d, of VSS generated
in the WWTP remains as non-biodegradable "cell debris." This cell
debris is the major portion of the nbVSS, which along with the
inert inorganics comprises sludge and exits the WWTP.
[0107] The fraction of total organic carbon ("TOC") in VSS that is
completely biodegradable (1-f.sub.d) leaves as carbon dioxide,
where f.sub.d is the non-biodegradable fraction. The process of
waste stabilization involves the oxidation of organic material by
bacteria with the production of carbon dioxide and water. Thus,
about 50% of the inbound BOD is converted to gas (CO.sub.2 and
N.sub.2) and water according to equation below. This is called
"burn" or "mass to gas." Consequently, the biomass synthesis yield
is typically less than unity.
biomass synthesis yield , Y = g biomass produced g substrate
consumed ##EQU00001##
[0108] At WWTP scale, on a day to day basis, one can define the
Yield to be the
Y = tons of dry solids out tons of BOD in ##EQU00002##
[0109] Yield can vary greatly, but the most efficient WWTPs seem to
produce around half a ton of sludge for every ton of biodegradable
material they receive. Observed Yield can be much greater in many
cases, approaching or even exceeding unity.
[0110] Incoming biodegradable material and return activated sludge
become food for the microorganisms in the WWTP. The bacteria either
use the food for growth (replication) or for cellular maintenance.
A small population primarily in stationary phase will use the food
to maintain cellular functions (catabolism). A large population
primarily in log growth will use the food to produce more cell mass
(anabolism). Given a limited food supply, a larger population will
undergo more endogenous decay (predation on one another). The decay
rate per unit time is increased. In this way, loaded silica
polymers drive the system towards greater endogenous decay and
cause more mass to leave as gas. And more microbial activity means
more highly treated water.
[0111] The chemical formula for BOD is
C.sub.8H.sub.12O.sub.3N.sub.2 Conversion of BOD to cell biomass can
be accurately represented by the following balanced chemical
equation (Reaction 1).
C.sub.8H.sub.12O.sub.3N.sub.2+3O.sub.2.fwdarw.C.sub.5H.sub.7O.sub.2N+3CO-
.sub.2+H.sub.2O+NH.sub.3
[0112] Every 184 grams of BOD treated will produce 113 grams of
biomass. This exerts a stoichiometric oxygen demand, which
corresponds to three moles of oxygen for every mole of BOD treated.
This reaction produces about 0.61 g biomass/g BOD treated.
Conversely, 1.42 g of BOD is consumed for every 1 g of biomass
produced. Microbial growth produces off gassing of CO.sub.2 and
N.sub.2 and generates water.
[0113] The complete oxidation of biomass to carbon dioxide, water,
and ammonia can be accurately represented by a second balanced
chemical equation (Reaction 2).
C.sub.5H.sub.7O.sub.2N+5O.sub.2.fwdarw.5
CO.sub.2+2H.sub.2O+NH.sub.3
[0114] The first reaction goes essentially to completion, i.e.
assume 100% of the inbound BOD is stabilized and converted to
biomass during cell growth. However, the second reaction occurs to
the extent that consumes the biodegradable fraction (1-fd) of VSS
produced in Reaction 1. It is this second reaction that converts
VSS mass to gas thereby reducing the observed yield of outbound
solids further below the 60% biosolids yield from equation above.
If we consider only the first reaction, assume that it goes to
completion, and draw a boundary around the aeration basin, then the
stoichiometry makes clear some simple overall mass balances around
the aeration basins. The mass fraction of TOC in BOD is 96/184 or
52%. In other words, carbon makes up over 50% of the total BOD mass
to be treated. Similarly, there is available oxygen contained in
BOD. The mass fraction of BOD that is oxygen is 48/184 or 26%.
[0115] Carbon does not accumulate, but leaves the WWTP as either
gas or sludge. The fraction of TOC in BOD that leaves as gas is
36/96 or 37.5%. The balance of the TOC in BOD that remains captured
in biomass is 60/96 or 62.5%. It is this 62.5% that can be further
reduced to gas. Of the mass of BOD into the reactor, almost 10%
gets reduced to liquid water in the basins. a significant amount of
water is generated during microbial growth. Organic nitrogen
comprises 28/184 or 15% of the BOD mass load. Half of this 15% gets
converted through nitrification/denitrification to N.sub.2 gas in
Reaction 1. So adding 37.5% mass to gas due to carbon dioxide and
7.5% mass to gas due to nitrogen, means that about 45% of the total
inbound organic load to the WWTP is lost as gas as a result of the
first reaction alone. About 45% reduction of BOD mass inbound
indicates that the stabilization process (Reaction 1) alone should
give a biomass synthesis yield around 55% (or 0.55). Any
improvement in the reduction of the yield from the process occurs
as the resulting biomass is then further oxidized and gasified
through Reaction 2. Reaction 2 describes Endogenous Decay of the
biomass generated within the WWTP. Reaction 2, if complete, would
convert all the biomass generated into gas and water and half of a
mole of ammonia. In this case, sludge would contain only inert
inorganics and inert VSS that had entered the WWTP in the influent.
Influent streams with greatly different compositional
characterization, such as higher loading concentrations of BOD and
COD, and streams with much higher inert fraction in the influent
may show much higher biomass synthesis yields than the 0.5-0.6
range observed at MUD 109, as described here.
Example 1
[0116] A test facility was selected at the Municipal Utility
District ("MUD") #109 ("MUD109") in Humble, Tex. This specific WWTP
had an excellent record of meeting compliance and had undergone an
extensive capital improvement project a few years prior to the
study. The MUD109 wastewater treatment facility has an average
daily flow rate of 4.1 million gallons. In October 2014, the test
began with the introduction of DryLet.RTM. LIFT to the headworks of
the WWTP at a rate of 8 pounds per day, or a projected annual
consumption of 2,920 pounds/year. Samples were collected and
analyzed, and flow and operation conditions were monitored for the
entire test period. These additional samples and analytics
augmented the standard analytics performed by an external
laboratory. The test period covered a total of seven (7) months,
from October 2014 through April 2015. The test, its methodology,
the data analysis, and the results are described herein.
[0117] The performance of the DryLet.RTM. LIFT product shows an
estimated 30% reduction of sludge and a 43% polymer reduction. The
economic benefit (see Table 1C) covers four key value drivers for
sludge reduction including sludge disposal, polymer use, equipment
life, and equipment maintenance costs.
TABLE-US-00003 TABLE 1C Table 1 C - Value Proposition Savings
Annual Annual Annual per Pound Value Driver Cost Cost Savings of
DryLet .RTM. Sludge Disposal $146,000 $102,000 $44,000 $15 Polymer
Use $35,000 $19,600 $15,400 $5 Equipment Life $52,000 $43,000
$9,000 $3 Equipment $35,000 $23,750 $11,250 $4 TOTALS $268,000
$188,350 $79,450 $27
[0118] Data from the historical operation of the WWTP was used as
the baseline data to compare the data from the system deploying the
Dry Let.RTM. LIFT product during the test time period. Table 2
presents the various data points collected for the analysis
presented herein.
TABLE-US-00004 TABLE 2 Aeration Outbound basin Effluent solids
Description Influent data data data data Historical BOD MLSS BOD
Number of From TSS SVI TSS hauls/month Operator VSS Daily NH.sub.3
(Assume 2009-2014 DO Sample DO constant pH TSS pH 14.27 2 samples/
DO Daily wet short month BOD Sample tons/haul) Daily Flow 2
samples/ 14.08% solids Recorded month everyday DO Analyzed every 3
minutes Test Period BOD BOD BOD Number of Test TSS TSS TSS
hauls/month America VSS VSS NH3 (Manifest Inc. DO DO DO data for
Oct 2014- pH pH pH wet short tons May 2015 Daily SVI Daily produced
sample Daily sample for each (M-F) sample (as reported haul) Daily
(M-F) + by STS) 14.08% solids flow + STS data 38 samples STS data
(see above) over 3 month (see above) period collected by Test
America
[0119] A sludge accounting model focuses on the outbound biosolids
production, and relates the mass produced to the mass of BOD load
inbound to the WWTP by the Biomass Synthesis Yield calculated
herein as Yield=mass of sludge produced per mass of BOD in the
influent. The focus of the analysis presented here is predicated on
estimates of loads and corresponding solids production, and the
goal was to enhance data collection during the test of inbound
concentrations and outbound weights. Effluent data remained
unchanged and provided proof of ongoing Compliance of Operations.
Process data provided a more detailed look at basin dynamics.
[0120] Plant Supervisory Control and Data Acquisition have retained
the results of two BOD grabs from the Atascocita Joint Operations
Board influent for each month dating back 5 years. These samples
have always been taken at the beginning and the end of the middle 2
weeks of each month. STS operator's reports also compute an Average
Daily Flow rate (ADF) for each month. (Flow
rate).times.(Concentration) gives mass loading and allows the
calculation of an estimated Load to the WWTP during any given
month; and, in fact can be averaged over the days of each month to
produce an estimated daily load to the WWTP. Given the estimated
load to the WWTP during each month of the test and the resulting
solids, and those same months' estimated load and solids production
from past records, a Yield factor was calculated, which describes
higher performance as being associated with a lower yield.
Historical biosolids production data for the 5 years preceding the
test were limited to the recorded number of hauls per month. These
hauls are taken to contain the average tonnage computed during the
test period of 14.27 wet tons per haul. For a 3-month period early
in the test, the filter cake was analyzed for moisture and
percentage solids contents. The cake grabs were only taken on days
with no precipitation so that rainfall could not affect the percent
moisture. The cake remained almost exactly 85% water content.
Solids were reported consistently as 150,000 ppm, or 14% dry
solids. As a result, all net wet tonnage of sludge reported on
Sludge Haul Manifests was taken to contain:
0.1408.times.(Net wet sludge in short tons)=(Dry solids in short
tons).
[0121] During the test, the influent BOD as measured in milligrams
per liter, was recorded far more frequently than in the past using
first a composite sampler and later with grab samples. The test
sampled for BOD in the influent about 20 times per month, having
been scheduled for 5 days a week. As shown in FIG. 1, the average
BOD for the Atascocita WWTP facilities exhibited an increasing
concentration of BOD (mg/l) over the period from August 2013
through March 2015. However, the average daily flow (ADF) was shown
to be decreasing. This suggests higher concentration of BOD related
to water conservation utilities in the average home. However, the
average total mass of BOD saw little change. The average daily flow
(ADF) plot shown in FIG. 2 illustrates a trend of decreasing water
usage for waste and suggests that water conservation is being
achieved through a combination of household utilities and changing
water consumption habits. The mass balances indicate that resulting
average BOD load per month has changed very little. The yield
analysis takes into account any variability in loading because it
calculates a "normalized" load.
[0122] The DO in the influent grab samples varies greatly from day
to day and may represent cycles of aerobic/anaerobic booms and
busts in the collection system pipes. DO grab samples from the
basins and the splitter box fell within the operational set point
range set by the operators. TSS and VSS in the influent were
tracked along with BOD in the influent. (TSS-VSS) gives the Inert
Inorganic load to the WWTP. The Inorganic Suspended Solids
(TSS-VSS) comprised roughly 10-15% of the solids load. TSS and VSS
were also tracked in the basins and at the splitter box. There was
no significant change in the inert inorganic fraction to the WWTP
or in its basins during the test. Grab samples were extracted from
various locations in the WWTP to examine the role of Suspended
Solids, BOD, and DO in unit operations, including but not limited
to, from the Influent Rapid Mixing Channel, from the aeration
basins themselves, and at the splitter box after the basins and
before the clarifiers. The grab values reported for the splitter
box were used in all basin data tabulation because this is the same
location that STS has always used for their bi-monthly basin grabs
for TSS and BOD.
[0123] The following on-site measurements were recorded-number of
bins of sludge filled per day, date for changing a polymer feed
drum, "Cook-off" test used to calculate MLSS (mg/l), "Set-test"
used to calculate SVI (Sludge volume index) (ml), Blanket height in
the 2 clarifiers, and Pounds of product applied each day by STS (8
lbs/day). Finally, Magna Flow records provided manifests describing
each 20 yd.sup.3 box that was taken for disposal at landfill. Each
manifest recorded the Gross Vehicle Weight, Curb Weight, and the
Freight on Board, with the waste content appearing as Short Tons.
The average weight of a box of sludge was 14.35 tons per 20
yd.sup.3 box. Records for the test period and all manifests for
previous years produced this same average.
Yield Analysis
[0124] A historical benchmark, or baseline, was established for
biosolids yield and then this yield was compared to the yield
calculated from WWTP test data with the DryLet.RTM. product. Yield
calculation is effected by the data sources for Input/Output (I/O)
to the mass balance: A simple approach ignores the Input (BOD load)
and looks only at the Output (number of hauls) produced during the
test (Raw sludge haul accounting).
Simple Sludge Haul Accounting--Historical Averages and Test Period
for Months November Through May
TABLE-US-00005 [0125] TABLE 3 Test period Historical Average Test
period (January Reduced Month (5 years) (Actual) correction) hauls
November 20 15 15 5 December 26 18 18 8 January 22 33 19* 3
February 22 15 15 7 March 24 16 16 8 April 28 21 21 7 *14 hauls
subtracted in January for digester inventory drawdown, 8 to 10 feet
of freeboard 2.0% solids
[0126] From Table 3, the aggregate number of hauls taken as a
historical average for months November through May totaled 142. The
total hauls for the same months during the test period totaled 104.
The net percent reduction is 26.5% on the number of hauls over the
same period from November through May. Excluding January, the net
percent reduction is 28.8% over the same period.
Simple Sludge Haul Accounting--Previous Period (November 13-May 14)
and Test Period for Months November Through May
TABLE-US-00006 [0127] TABLE 4 Previous year Reduced Month (Nov
2013-May 2104) Test Period hauls November 24 15 9 December 23 18 5
January 26 19* 7 February 19 15 4 March 24 16 8 April 46 21 25
[0128] From Table 4, the aggregate number of hauls taken as a
historical average for months November through May totaled 162. The
total hauls for the same months during the test period totaled 104.
The net percent reduction is 35.8% on the number of hauls over the
same period from November through May. Excluding January, the net
percent reduction is 37.5% over the same period.
[0129] The following methods were used for yield analysis. A first
method uses the same limited data points as the historical record
retention to estimate I/O response during the test (Yield
analysis). A second method uses a more accurate assessment of the
load to the WWTP during the test by sampling BOD more frequently to
improve the estimate of I/O response (Yield analysis). A third
method uses all the influent BOD sample results to generate a
global average of BOD concentration during the test from October to
May. This concentration can then be used as the daily concentration
for loading calculations throughout the test, and only the ADF
would change from day to day (Yield analysis). Another method
incorporates actual haul weight data to obtain a more accurate
assessment of the Output produced during the test rather than
assuming a 14.1 ton average per haul (Yield analysis).
TABLE-US-00007 TABLE 5 Stream Method 1 Method 2 Method 3 Influent
Operator Test Test (Mass In) analytical: America BOD America BOD
Average analytics: analytics: of 2 BOD monthly Test period samples
per month average (global) average Daily Flow as Daily Flow as
Daily Flow as recorded by recorded by recorded by Operator Operator
Operator Outbound Number of hauls Number of hauls Number of hauls
(Mass Out) Average weight of MagnaFlow Inc., MagnaFlow Inc., each
haul over test actual manifest actual manifest (14.27 short tons
per tonnage tonnage haul) Average percent Average percent Average
percent solids solids solids (14.08 (14.08 (14.08 percent dry
percent dry percent dry solids per haul) solids per haul) solids
per haul)
[0130] Table 5 summarizes the differences in the analytic methods
used to calculate Yield of sludge per short ton of BOD:
[0131] Yield Analysis: Historical Average Using Method 1.
[0132] The following tabulated data was calculated using the
criterion of Method 1. The percent yield was determined for each
month and ranged from 35% to 47%.
Monthly Total BOD ( ST ) STS , BOD 2 samples = ( AVG . BOD 2
.times. Daily Flow ) ##EQU00003## Monthly Dry Solids ( ST ) AVG ,
CAKE = ( Number of Hauls each month ) .times. 14.27 [ Average
weight of wet sludge per haul in short tons ] .times. 0.1408 [
Average mass fraction of solids ] ##EQU00003.2## Yield ( Method 1 )
= Monthly Dry Solids ( ST ) AVG , CAKE Monthly Total BOD ( ST ) STS
, BOD 2 samples ##EQU00003.3##
TABLE-US-00008 TABLE 6 Historical Average from 2009 through 2014
Average Total Total Total Historical Accum. ADF BOD Sludge Dry
solids Percent # Month Period Flow (MGD) (MGD) (ST) (ST) (ST) Yield
hauls November November ('09-'13) 129 4.3 100 291 41 41% 20
December December ('09-'13) 138 4.4 120 371 52 44% 28 January
January ('10-'14) 135 4.4 131 316 45 34% 22 February February
('10-'14) 125 4.5 96 312 44 46% 22 March March ('10-'14) 136 4.4
123 335 47 38% 24 April April ('10-'14) 130 4.2 119 395 56 47% 28
Totals 793 688 2020 284 142 w/o January 119
[0133] The historical data presented in Table 6 is used to compare
the test period data and analysis utilizing Methods 1, 2, and 3.
The following sections illustrate the changes in the yield during
the test period using DryLet.RTM. LIFT.
[0134] Yield Analysis: Test Period (Method 1) Versus Historical
Average
[0135] The following tabulated data was calculated using the
criterion of Method 1. The percent yield was determined for each
month and ranged from 26% to 37%.
Monthly Total BOD ( ST ) STS , BOD 2 samples = ( AVG . BOD 2
.times. Daily Flow ) ##EQU00004## Monthly Dry Solids ( ST ) AVG ,
CAKE = ( Number of Hauls each month ) .times. 14.27 [ Average
weight of wet sludge per haul in short tons ] .times. 0.1408 [
Average mass fraction of solids ] ##EQU00004.2## Yield ( Method 1 )
= Monthly Dry Solids ( ST ) AVG , CAKE Monthly Total BOD ( ST ) STS
, BOD 2 samples ##EQU00004.3##
TABLE-US-00009 TABLE 7 Method 1 Average Total Total Total Accum.
ADF BOD Sludge Dry solids Percent # Month Period Flow (MGD) (MGD)
(ST) (ST) (ST) Yield hauls November November '14 114 3.8 114 214 30
26% 15 December December '14 126 4.1 123 257 36 29% 18 January
January '15 127 4.1 100 266 37 37% 19 February February '15 103 3.7
110 214 30 27% 15 March March '15 130 4.2 125 228 32 26% 16 April
April '15 124 4.1 116 300 42 36% 21 Totals 723 689 1479 208 104 w/o
January 85
[0136] Table 7 presents the comparison of the historical and test
period yields using Method 1.
TABLE-US-00010 TABLE 8 Historical Average Method 1 % Month Yield
Monthly Yield Chg. November 44% 26% 40% December 44% 29% 34%
January 35% 37% -6% February 46% 27% 40% March 38% 26% 33% April
47% 35% 25%
[0137] As shown in Table 8, the net percent reduction in yields
using the averages for each period (historical and test period)
results in a 26% decrease. When the yield is calculated on an
overall mass balance of BOD load and Dry Solids for the same period
the reduction in the yield is 27%. Excluding January 2015 for both
cases results in a yield reduction of 33% and 30%,
respectively.
[0138] Yield Analysis: Test Period (Method 2) Versus Historical
Average.
[0139] The following tabulated data was calculated using the
criterion of Method 2. The percent yield was determined for each
month and ranged from 26% to 37%.
Monthly Total BOD ( ST ) TA , BOD 20 samples = ( AVG . BOD 20
.times. Daily Flow ) ##EQU00005## Monthly Dry Solids ( ST ) ACTUAL
, CAKE = ( Actual Manifest Wet Sludge Weight ) .times. 0.1408 [
Average mass fraction of solids ] ##EQU00005.2## Yield ( Method 2 )
= Monthly Dry Solids ( ST ) ACTUAL , CAKE Monthly Total BOD ( ST )
TA , BOD 20 samples ##EQU00005.3##
TABLE-US-00011 TABLE 9 Method 2 Average Total Total Total Accum.
ADF BOD Sludge Dry solids Percent # Month Period Flow (MGD) (MGD)
(ST) (ST) (ST) Yield hauls November November '14 114 3.8 109 205 29
26% 15 December December '14 126 4.1 107 282 40 37% 18 January
January '15 127 4.1 133 266 37 28% 19 February February '15 103 3.7
115 236 33 29% 15 March March '15 130 4.2 126 240 34 27% 16 April
April '15 124 4.1 117 302 43 36% 21 Totals 723 708 1530 216 104 w/o
January 85
[0140] Table 9 presents the comparison of the historical and test
period yields using Method 2.
TABLE-US-00012 TABLE 10 Historical Average Method 2 % Month Yield
Monthly Yield Chg. November 44% 26% 40% December 44% 37% 16%
January 35% 28% 20% February 46% 29% 37% March 38% 27% 30% April
47% 35% 24%
[0141] As shown in Table 10, the net percent reduction in yields
using the averages for each period (historical and test period)
results in a 26% decrease. When the yield is calculated on an
overall mass balance of BOD load and Dry Solids for the same period
the reduction in the yield is 26%. Excluding January 2015 for both
cases results in a yield reduction of 28% and 25%,
respectively.
[0142] Yield analysis: Test Period (Method 3) versus Historical
Average. The following tabulated data was calculated using the
criterion of Method 3. The percent yield was determined for each
month and ranged from 27% to 36%.
TABLE-US-00013 TABLE 11 Method 3 Average Total Total Total Accum.
ADF BOD Sludge Dry solids Percent # Month Period Flow (MGD) (MGD)
(ST) (ST) (ST) Yield hauls November November '14 114 3.8 109 205 29
27% 15 December December '14 126 4.1 120 282 40 33% 18 January
January '15 127 4.1 121 266 37 31% 19 February February '15 103 3.7
98 236 33 34% 15 March March '15 130 4.2 125 240 34 27% 16 April
April '15 124 4.1 118 302 43 36% 21 Totals 723 691 1530 216 104 w/o
January 85
[0143] Table 11 presents the comparison of the historical and test
period yields using Method 3.
TABLE-US-00014 TABLE 12 Historical Average Method 3 % Month Yield
Monthly Yield Chg. November 44% 27% 40% December 44% 33% 16%
January 35% 31% 20% February 46% 34% 37% March 38% 27% 30% April
47% 35% 24%
[0144] As shown in Table 12, the net percent reduction in yields
using the averages for each period (historical and test period)
results in a 24% decrease. When the yield is calculated on an
overall mass balance of BOD load and Dry Solids for the same period
the reduction in the yield is 24%. Excluding January 2015 for both
cases results in a yield reduction of 27% and 24%,
respectively.
[0145] Yield Analysis: Steady State Period (Method 3) Versus
Historical Average.
[0146] The steady state period is defined by the dates of Mar. 11,
2015 through Apr. 30, 2015. This is the period where the change in
TSS in the aeration basin was approximately 9,500.+-.1,500
milligrams per liter or a range of 8,000 to 11,000 mg/L. The
following tabulated data was calculated using the criterion of
Method 3.
TABLE-US-00015 TABLE 13 Yield Analysis for Steady State Period
(March, April, & May) Total Total Total Mass Mass Mass % BOD
Sludge Dry solids Percent chg. Data Set (ST) (ST) (ST) yield Yield
Historical Average 209 641 90 43% N/A Steady state test period 198
472 67 34% 22.3%
[0147] Table 13 presents the comparison of the historical and test
period yields using Method 3.
TABLE-US-00016 TABLE 14 Historical Average Method 3 # Month Yield
Monthly Yield Chg. March.-April. 43% 34% 22.3%
[0148] As shown in Table 14, the net percent reduction in yields
using the averages for each period (historical and test period)
results in a 22.3% decrease.
Operational Factors and Digester Drawdown
[0149] In the last half of December into January, operators decided
to draw down their already full digester, as they prefer to operate
with some available freeboard capacity as a buffer. In this same
period, they raised the wasting rate to 40%. The increased wasting
flushed through the system in January and when combined with the
digester drawdown, caused a huge spike in hauls in January. The
sludge inventory in the digester had to be accounted for. The
digester was at full capacity when the study period started and it
continued to be full until January. It was then emptied throughout
the month as confirmed by the sludge haul manifests. Therefore, the
mass of 25 ST of dry sludge that was hauled, but not produced in
January was subtracted from the dry metric tons for the month of
January. A similar situation occurred for much of April, because
there was concern about the high solids levels. These two changes
probably resulted in unnecessary sludge production that makes the
January and April observed yields both on the high side, as seen in
FIGS. 3A and 3B.
[0150] The historical trend (higher plotted line) and the test
period trend (lower plotted line) in FIG. 3A show the number of
hauls per month. The amount of solids wasted is the product of the
wasting rate and the wasting concentration. When solids levels are
elevated, operators must pay more attention to process control,
particularly to the wasting rate. There are two periods where the
waste activated sludge (WAS) rate was increased during the period.
Interestingly, the plot shows similar seasonality between to the
two offset by a total reduction in number of hauls for each and
every month. The graph in FIG. 3B shows the trend for the
bio-solids yield and the performance for each month when the WAS
rate was increased for a period of time. The period of use of
DryLet.RTM. product reduced the bio-solids yield from a low of 23%
to a high of 54%. Month 1 is the comparable month with Month 2
showing the greatest decrease by 54% and month 3 exhibited the
least of 23%.
[0151] Yield calculated based on the four months was 0.29,
resulting in a 32% reduction of sludge. As shown in Table 15, the
percent reduction calculated from the various methods gives a range
of results from 24% to 37%, with high values corresponding to cases
that exclude January, and the lowest values corresponding to the
cases in which no raw data was excluded. The results then for
sludge reduction can be reported with an extremely high degree of
confidence as being 30%+/-8%, and most likely 30%+/-5% with a very
good degree of confidence. Average of these calculated values is
28.2%.
TABLE-US-00017 TABLE 15 % Reduction METHOD HIGH LOW Sludge haul
(Historical) 28.8 26.5 Sludge haul (Last Year) 37.5 35.8 Method 1
32.8, 29.8 25.8, 26.9 Method 2 28.1, 26.4 25.1, 26.3 Method 3 27.6,
24.6 24.4, 24.6
Equipment Life and Maintenance
[0152] The reduction of sludge produced has the ancillary effect of
extending the life of sludge-handling equipment, namely the belt
presses.
Belt Press Useful Life Extension, Associated Equipment
[0153] Replacement of the smaller (Ashbrook) belt press and polymer
system is currently estimated at around $667,000 including
contingency and engineering. Similarly, the purchase, installation
and engineering costs for the larger (Andritz) press totaled
approximately $550,000 in 2005 and $672,048 adjusted for
inflation.
[0154] Using the straight-line depreciation method, the capital
savings on the presses were estimated to be $8,000 a year for the
Ashbrook and $8,070 for the Andritz. The projected depreciation is
shown in FIGS. 4 and 5. In FIG. 4, the smaller belt press (Ashbrook
Press) depreciation lines are shown for the useful life under
standard operating conditions (Existing Depreciation) and the
potential useful life under operating conditions while using the
product (Projected Depreciation). The reduction in bio-solids
through the use of DryLet.RTM. product will extend the life of the
Ashbrook press by 10 years. In FIG. 5, the larger belt press
(Andritz Press) depreciation lines are shown for the useful life
under standard operating conditions (Existing Depreciation) and the
potential useful life under operating conditions while using the
product (Projected Depreciation). The reduction in bio-solids
through the use of DryLet.RTM. product will extend the life of the
Andritz press by 10 years.
[0155] To perform the analysis the depreciable asset cost and the
straight-line depreciation rate were calculated.
Depreciable Asset Cost = Initial Cost - Residual Value ##EQU00006##
Depreciation Rate = 1 Useful life ##EQU00006.2##
[0156] They were multiplied to obtain the existing annual
depreciation rate:
Existing Annual Depreciation=Depreciation Rate*Depreciable Asset
Cost
[0157] The annual depreciation rate is then subtracted from the
value of the press every year to project its future value. To
obtain the projected depreciation the existing depreciation was
then multiplied by 70% (reflecting a 30% reduction in use).
Projected Depreciation=Existing Depreciation (1-% reduction in
use)
Belt Press Maintenance Cost Reduction.
[0158] The cost savings on belt press maintenance were calculated
based on the percentage reduction of biomass yield during the study
period. The total amount spent on maintenance and repairs on the
belt pressed and associated equipment from the bookkeepers report
from fiscal years 2009 to 2013 was adjusted for inflation to 2015
U.S. Dollars and an average yearly cost calculated as shown in
Table 16. It was then multiplied by the percent reduction of
biomass yield to obtain the 2015 projected expenses. Finally, the
2015 projected savings was calculated by taking the difference of
the average and the projected expenses. Assuming a 30% reduction in
maintenance and repairs based on the reduction in sludge production
from using the DryLet.RTM. product, annual savings were thus
calculated.
TABLE-US-00018 TABLE 16 Belt Press Inflation Fiscal year
Maintenance Adjusted to 2015 June 2009-May 2010 $21,148 $23,144
June 2010-May 2011 $42,175 $44,744 June 2011-May 2012 $12,983
$13,494 June 2012-May 2013 $66,393 $68,012 June 2013-May 2014
$38,412 $38,721 5-year Average $36,222 $37,623 2015 Projected
Savings (30%) $11,287 2015 Projected Expenses $26,336
[0159] Polymer Used as Flocculating Agent.
[0160] The polymer, which is used to aid in dewatering the sludge,
was supplied just before the presses. While this feed rate is
adjustable, it is always entrained into the wasting stream to the
presses. A reduction in polymer use occurs naturally from creating
less pressed sludge. Historical data for polymer usage was limited
to the number of drums purchased within a year prior to the study
period. The drums have a volume of 55 gallons, so an average of
gallons per month was calculated.
Historical U sage ( gal month ) = Number of drums invoiced month 55
( gal drum ) ##EQU00007## Average drum life ( day drum ) = 55 ( gal
drum ) H istorical usage ( gal day ) ##EQU00007.2##
[0161] Accurate tracking of polymer use was achieved by marking the
date the polymer drum was changed. This was performed beginning
February 5th and lasting until April 14th. An estimate of gallons
per month was then calculated by dividing 55 gallons in a drum over
the time period it lasted.
Study period usage ( gal day ) = 55 gal days between drum change
##EQU00008## Study period usage ( gal month ) = Study period usage
( gal day ) days of the month ##EQU00008.2##
[0162] The study period average was then compared to the average
for the previous year to obtain a percent reduction in use.
Percent Reduction ( % ) = Study period usage ( gal month ) -
historical usage ( gal month ) H istorical usage ( gal month )
##EQU00009##
[0163] The cost savings on polymer usage were calculated based on
the percentage reduction of polymer use during the study period.
The total amount spent on "Polymer/Sludge Treatment" from the
bookkeepers report from fiscal years 2009 to 2013 was adjusted for
inflation to 2015 U.S. Dollars and an average yearly cost
calculated. It was then multiplied by the percent reduction of
polymer use to obtain the 2015 projected expenses. Finally, the
2015 projected savings was calculated by taking the difference of
the average and the projected expenses. The polymer, which is used
to aid in dewatering the sludge, is fed just before the presses.
While this feed rate is adjustable, it is always entrained into the
wasting stream to the presses. A reduction in polymer use occurs
naturally from creating less pressed sludge. Table 17 shows the
historical polymer usage, while Table 18 shows the study period
tracking of polymer use.
TABLE-US-00019 TABLE 17 Report Month Drums Gallons per Month
October 2013 4 220 November 2013 4 220 December 2013 3 165 January
2014 0 0 February 2014 3 165 March 2014 0 0 April 2014 3 165 May
2014 5 275 June 2014 5 275 July 2014 4 220 August 2014 0 0
September 2014 0 0 Average 3 142
TABLE-US-00020 TABLE 18 Date Gallons Gallons per Day Gallons per
Month Feb. 5, 2015 N/A N/A N/A Feb. 24, 2015 55 2.89 81 Mar. 11,
2015 55 3.67 114 Apr. 14, 2015 55 1.62 50 Average 2.73 81
[0164] Table 19 shows the comparison of the historical and study
period polymer use. A reduction of 43% was documented during the
study period along with a corresponding extension in drum life.
TABLE-US-00021 TABLE 19 Polymer Use Gallons per Month Drum Life
(Days) Historical 142 12 Study Period 82 20 % Reduction -43%
+43%
TABLE-US-00022 TABLE 20 Polymer/Sludge Inflation Fiscal year
Treatment Adjusted to 2015 June 2013-May 2014 $27,670 $27,435 June
2012-May 2013 $71,332 $71,872 June 2011-May 2012 $15,613 $15,962
June 2010-May 2011 $36,452 $38,037 June 2009-May 2010 $19,425
$20,910 Average $34,098 $34,843 2015 Projected Expenses $20,016
2015 Projected Savings $14,827
[0165] Table 20 shows the cost of Polymer/Sludge Treatment per
fiscal year, the adjustment to 2015 U.S. Dollars and the projected
savings for a 43% reduction in polymer use.
[0166] As shown in Table 21, there was minor variation on energy
usage on a month-to-month basis and no net change in energy usage
over the study period. This can also be seen on FIG. 6, where the
5-year historical monthly average for power (kWh) use from running
the aeration blowers was compared against the monthly power
consumption (kWh) during the testing period. The overall power use
was 2% less than that during the 5-year historical monthly average.
This is significant because the use of DryLet.RTM. product
increased the mass under aeration almost by 300%. One would have
expected that more power would have been required significantly
through more oxygen consumption. Increased microbial growth
increases the blower demand; but in this case, no increase in
electrical consumption was detected. Whatever increase in oxygen
demand that occurred in the system was offset by operational
improvement brought about by blower control tuning.
TABLE-US-00023 TABLE 21 Historical Average Study Period Month
(2009-2014), in kWh (2014-2015), in kWh % Reduction October 738 772
5% November 719 678 -6% December 768 796 4% January 821 810 -1%
February 713 700 -2% March 777 753 -3% April 770 760 -1% May 742
736 -1% June 715 738 3% July 721 713 -1% Average 748 746 0%
Reduction in Waste Product
[0167] In FIG. 7, the 5-year monthly average of total dry solids is
plotted against the total dry solids produced for each month during
the testing period. For each and every month, the WWTP generated
less dry solids for waste disposal. The results of the study show a
cumulative and sustained 30% reduction of sludge compared to
historical WWTP operations. A variety of methods of analysis all
produce the same result indicating a high degree of confidence in
the analysis. The study shows that Dry Let.RTM. LIFT reduced raw
sludge production by 30%+/-5%.
[0168] The graph in FIG. 8 illustrates the dramatic and surprising
change in microbial growth rates in the aeration basins over the 8
months. The plots represent the TSS and the fraction of the TSS
that is the VSS. In the case of the scatter plots, the TSS is the
higher values with the VSS just below the corresponding TSS value
moving along the time axis. On average, the VSS accounted for
approximately 80% of the TSS during the entirety of the test. The
use of DryLet.RTM. product increased the carrying-capacity of the
WWTP almost by 300%. As shown by the plot, the TSS in the aeration
basin increased from a normal operating range of 2,500 to 3,500
mg/l to a new range achieved through the use of DryLet.RTM. product
of 8,000 to 11,000 mg/l. This graph demonstrates the classic
sigmoidal shape associated with an increasing microbial population.
The population increases from a low level between 0 and 50 to 60
hours and then rapidly increases between about 60 hours to 180
hours, and then plateaus. There are some fluctuations around this
pattern, due operational variations, but it follows that trend for
both TSS and VSS.
[0169] As the microbial population ramps up during a transitional
period then mass is accumulated in the system as shown in FIGS. 9
and 10. Focusing on the last three months indicates that a new
steady state had been achieved. Original MLSS readings were in the
range of 2,500-3,500 mg/l. In the new steady state system, levels
were in the range of 9,000-11,000 mg/l for TSS. FIG. 9 shows the
significant change in the new operating condition or set point of
the WWTP. The lower line shows the average MLSS concentration
(mg/l) and the higher line is the average of the scatter plot of
data points. Special attention is placed on the large dip in the
scatter plot occurring around Day 196, where the WWTP experienced
heavy rain events. There was a quick response in the bioreactor as
shown by the increase rate of MLSS back to the new set point range
of 9,600 mg/l, which was a 2.times. to 3.times. increase in WWTP
carrying capacity from normal operating conditions. The higher
quantity of suspended solids indicates an increase microbial
population by a factor of 2.5 from the normal operation with the
application of the silica polymer containing microbes. In FIG. 10,
the graph of the mass under aeration shows the increasing trend of
the total mass during the testing period. The mass under aeration
increased by a factor of 3 and sustained this at steady state from
about Day 160 to Day 240. There was about a three-fold increase in
carrying capacity, which gradually increased from around 20 to 30
tons initially to over 70 to 80 tons in the aeration basin from the
start of the test period to about 160 days, when it stabilizes. The
increase in carrying capacity was almost three fold.
[0170] In this new steady state, over 70 short tons are under
aeration in the WWTP. However, after day 160, mass was no longer
accumulated in the WWTP. This period shows the same reduction in
amount of sludge produced and shows the same reduction in the Yield
factor that was observed during the transitional phase. The new
steady state was far outside of recommended ranges set forth by
regulatory agency guidelines. The WWTP response described here was
the result of 8 pounds of DryLet.RTM. product a day throughout the
test period. In this pilot study, the amount of solids was allowed
to climb slowly. It remains to be determined how quickly the
carrying capacity can be raised to this level or an even higher
level with perhaps a higher dose of the DryLet.RTM. product for
transitional periods followed by a smaller maintenance dose of 8
pounds.
[0171] Either way, the product showed the same 30% reduction after
the first month of application. The following savings table was
based on the performance of the product after the first month of
inoculation projected out to an annual basis. Table 22 focuses on
the four main value drivers centered on sludge reduction, and
conveys the value proposition for this embodiment of the method and
system.
TABLE-US-00024 TABLE 22 Operating Cost/Value Driver Result Sludge
Disposal 30% Reduction Polymer Usage 44% Reduction Press Equipment
Life 30% Reduction Press Maintenance 30% Reduction
[0172] The ancillary benefits of longer equipment life and reduced
maintenance on presses and associated equipment naturally arise
from simply performing the action of creating 30% less pressed
sludge. The polymer, which was used to aid in dewatering the
sludge, was fed just before the presses. While this feed rate was
adjustable, it was always entrained into the wasting stream to the
presses. No extrapolation was required to quantify polymer
reduction because operators tracked the rate of consumption.
Polymer consumption was reduced 44%.
[0173] As shown in FIGS. 11A-D, all of the key performance
indicators showed a steady and dramatic increase during the product
test period. FIG. 11A shows the TSS measured in the aeration basin
from October 2014 through April 2015. FIG. 11B shows the BOD
measured in the aeration basin from October 2014 through April
2015. FIG. 11C shows the VSS measured in the aeration basin from
October 2014 through April 2015. FIG. 11D shows the SRT calculated
from the analytical data and wasting rate of the WWTP over the
testing period from October 2014 through April 2015.
[0174] The analytical results of the effluent during the testing
period are shown in FIG. 12. The primary y-axis shows the
concentration of TSS (represented by squares) and the concentration
of BOD (represented by triangles). The secondary y-axis shows the
ammonia concentration (represented by triangles). During the
testing period the ammonia concentration was below the detection
limit of <0.10 mg/l, the TSS concentration was below detection
limits for most of the study at a value <2.0 mg/l, and the BOD
concentration was the majority of time below the detection limit of
<2.5 mg/l. The effluent measurements did not exceed any
permitted limit during the testing period. The WWTP remained
completely compliant throughout the 7-month test period during all
of these changes.
Effect on Sludge, Polymer, MLSS, BOD, SVI and SRT
[0175] There were dramatic changes in several key performance
indicators during the course of the product trial with no
excursions and no deleterious effects. In fact, the WWTP seemed to
run more smoothly with only one full time operator on-site most of
the time.
[0176] MUD 109 has two presses, a large one and a smaller one.
Historically, the "little press" was unable to handle all the
solids by itself. However, due to the significantly reduced amount
of sludge generated, the smaller press was used almost exclusively
during 5 of the 7 months of testing. The larger press required
repairs and spent most of the test period off-line. This was
apparently not possible before. As a result, the urgency to repair
the large press was removed.
[0177] Polymer was delivered by an LCM pump into the wasting stream
just before the presses. A logbook was maintained on-site to record
the number of days that a 55-gallon drum of polymer would last
before being emptied and replaced with a new drum. Customarily, one
such drum was expected to last about 7-10 days. After the first
month of the test, records show that each drum lasted longer; about
14 days on average, and some drums lasted up to 17 days.
[0178] Moreover, as shown in FIG. 13, the quality of the sludge was
superior. The image shows the sluice of the belt press disposing
waste biosolids into a standard waste bin. While the filter cake
remained about 85% moisture content, the operational aspects were
significantly improved. The cake fell from the belt presses in
large sheets of very uniform consistency. Consequently, the
operators spent less time hosing the belts down. The man hours
saved could be redirected to other operational and maintenance
duties.
[0179] Using the precipitated silica granules loaded with
microorganisms increased several aspects of the WWTP as shown in
Table 23. For example, without limitations, sludge production and
consumption of flocculating agents reduced 30% and 40%
respectively, carrying capacity (MLSS) raised 3.5.times., BOD in
the basins raised 8-10.times., and observed solids retention time
increased at least about 5.times..
TABLE-US-00025 TABLE 23 Process Variable Before After TSS in basin
2,500-3,800 mg/l 9,000-11,000 mg/l DO in basin 2.0-3.5 mg/l 2.0-3.5
mg/l Recycle Ratio (RAS/Q) Roughly 100% Roughly 100% Blanket Height
1 foot in 10 feet SWD 1 foot in 10 feet SWD SRT 10 days 50 days SVI
Roughly 100 Roughly 100 BOD in basins 400-500 mg/l 3,000-4,000
mg/l
[0180] BOD grab samples from the aeration basins also increased
dramatically. At the outset, BOD in the basins averaged 400-500.
After a few months, this value increased to 3,000 or 4,000 at
times. This trend may well support the notion that a much larger
microbial population would release far more enzymes and VFAs into
the water. These enzymes and VFAs play a significant role in the
lysis of inactive biomass, which causes intracellular constituents
to become solubilized. The TSS increased as shown in FIG. 14.
Lastly, the calculated SRT increased from 9-10 days to a staggering
and unexpected 50 days. This value has not been previously known or
demonstrated in the industry.
Effect on Clarifier Solids Flux
[0181] While the aeration basins serve as chemostat bioreactors,
the secondary clarifiers function strictly for settling suspended
solids. Clarifier state point analysis indicated that higher MLSS
in the WWTP results in a higher solids loading rate to the
clarifiers. Higher mass flux requires that the operator raise the
RAS rate to keep a comfortable blanket height. In this WWTP, 2 of 3
clarifiers are in use. Adding the third clarifier would reduce the
mass flux through each clarifier 33% over the case with only 2
clarifiers. The entire test period utilized only 2 clarifiers, so
it stands to reason that the settling capability of the WWTP was
not a limiting factor, even though MLSS more than tripled.
[0182] The concern as MLSS increases is that without good settling
characteristics, solids would spill out at the overflow. But, in
this instance, the clarifiers never failed, and effluent remained
in compliance throughout the test. The 30-minute set test was
employed on-site as a rough but reliable indicator of good settling
characteristics. The 30-minute set was then divided by the MLSS and
multiplied by 1,000 to give the SVI. So the solids height after 30
minutes was expected to double if MLSS doubles for the same SVI.
But, in this instance, the blanket height also remained constant
and presented no challenge to control. STS operators were easily
able to adjust RAS and maintain a relatively low blanket height (1
foot) in the presence of a higher solids loading rate, indicating
excellent settlability. DO Control and Disinfection
[0183] MUD 109 uses a circle chart in the control room to display
DO in the aeration basins. Initially, a discrete meter, which took
readings only once every 3 minutes, was used at MUD 109 and this
had kept the blower use "between the ditches." The chart began to
show a lot of "paint brushing" or cycling on and off frequently as
the MLSS increased. This indicated that perhaps the oxygen uptake
rate had been significantly increased as the bacterial population
became more active. While increased activity suggests a greater
oxygen requirement, there was the question of efficiency of oxygen
delivery coupled with biological uptake. Oxygen (air) was blown in
great excess. But, upon the installation of a continuous meter, the
DO charts showed a marked decrease in overshoot and undershoot of
the set point range. The frequent cycling stabilized as a result.
The new charts with the new continuous meter were much smoother
circles showing a far more energy efficient oxygen delivery.
[0184] The operators were able to substantially reduce blower
requirement by simply staggering set points and shifting both the
upper and lower set points down half a point. The tuning capability
appeared to relate to accelerated oxygen uptake rate. In fact,
having "more horsepower" in a WWTP carries with it the potential to
bring about continuous improvement in blower operation and
increased process efficiency that would not be possible with a more
sluggish microbial population. Ammonia remained below the limit of
detection throughout the entire test. BOD was also frequently below
MDL. More biological activity corresponds to more highly treated
water. This raises the possibility that more microbes and more
enzymes in the water might reduce chlorine and dechlor disinfection
treatment requirements. These represent an enormous fraction (25%)
of the WWTP operating costs. A 10% reduction in chlor/dechlor was
very significant. The parameters around sludge and polymer
reduction present a clear savings to the WWTP. Furthermore, it is
conceivable that blower tuning and chemical disinfection tuning
could easily increase the value proposition.
[0185] Extending the life of the press by using it 30% less
prolongs the equipment's life cycle and delays its inevitable
replacement. If municipalities can get more throughputs and more
microbial activity with the existing WWTP, the efficiency of the
existing wastewater infrastructure is increased. Increasing the
effective carrying capacity of an existing WWTP would postpone
impending capital improvement projects, particularly those related
to expansion and press replacement. The time value of money not
spent until later is a positive cash flow over the capital
improvement project budgets on financials.
Qualitative Benefits
[0186] As stated m the introduction, reducing biosolids makes
wastewater treatment more sustainable and more environmentally
responsible. Less hauling means less fuel spent and a smaller
footprint for disposal. Less hauling also means fewer trucks on the
roads and less stress on the infrastructure. The process of
pressing the solids is a major function of the operator and
consumes a large portion of the time. Helping with ease of
operation by reducing the logistics of the outbound solids queue is
a logical conclusion. In this way, the product can possibly reduce
the total FTE allotted to larger facilities employing several or
many workers. A more robust microbial treatment will be more able
to absorb BOD step changes and toxic loads. The dose response curve
for these events will show a faster dampening factor with increased
metabolic activity. While a toxic shock load will still affect some
percentage of the population, a larger population will have more
viable microorganisms remaining after a kill.
[0187] In Example 1, the DryLet.RTM. LIFT product displayed a
robust impact on WWTP performance in many significant ways. Given
the large quantity of data acquired during the test, and the
dramatic changes to sludge production and several of the most
important process parameters, the beneficial sludge and polymer
reduction are attributed to DryLet.RTM. LIFT. DryLet.RTM. LIFT
began to reduce biosolids production after 30 days in the WWTP, and
had a sustained 30% reduction of sludge and a 44% reduction of
polymer use into the presses. By extension from reduced sludge
production, we must associate 2 additional savings to the WWTP from
the product: Longer equipment life, and reduced equipment
maintenance costs associated with the presses. Deeper examination
of bioprocess dynamics reveals Dry Let.RTM. LIFT caused an
astounding 3-3.5.times. increase in the carrying capacity of the
WWTP in terms of the microbial population as measured by VSS, TSS,
and BOD levels in the air-cut water of the basins. The product
caused no increase in electrical cost overall, and caused no
increase in blower run time. In fact, this study suggests that
increased carrying capacity could actually result in blower savings
in the future by positively affecting the oxygen uptake rate. The
strong positive performance of the DryLet.RTM. product for sludge
and polymer reduction, combined with the dramatic changes to the
process suggest that this technology could have the potential to
shift the current understanding of and operation in the Wastewater
Industry. This product can reduce the number of basins required at
a WWTP because of increased carrying capacity. Methods and products
described herein produce reduction in biosolids after about 30 days
and realize significant operational and potentially capital
improvement project savings while reducing the environmental impact
of Wastewater Treatment.
Additional Supporting Formulae and Modeling Methods
[0188] Monthly Sludge Hauls to Short Tons
Wet Sludge ( ST month ) = Sludge Hauls per month Average Tonnage
per Haul ##EQU00010## Wet sludge to Dry sludge ( 14 % solids )
##EQU00010.2## Dry Sludge ( ST month ) = Wet Sludge Percentage
solids ##EQU00010.3## Daily Influent BOD load ##EQU00010.4## BOD in
Load ( ST day ) = BOD in ( mg l ) ADF ( M gal day ) 3.785 ( Liters
Gal ) 9.07 10 8 ( ST mg ) ##EQU00010.5## Monthly Influent BOD load
##EQU00010.6## BOD in Load ( ST / month ) = BOD in Load ( ST / day
) days of the month ##EQU00010.7## Monthly Observed biomass yield
##EQU00010.8## o bserved biomass yield , Y obs = g biomass produced
g substrate consumed = Dry sludge ( ST / month ) BOD in Load ( ST /
month ) ##EQU00010.9## Yield Percent Reduction ##EQU00010.10##
Percent Reduction ( % ) = Y obs , hist - Y obs , study Y obs , hist
= 1 - Y obs , study Y obs , hist ##EQU00010.11## HRT
##EQU00010.12## Hydraulic Retention Time ( day ) = Volume of
Aeration Tank ( ft 3 ) Influent Flowrate ( M gal day ) ( M gal ft 3
) ##EQU00010.13##
[0189] By studying the substrate uptake rate, daily gas production,
gas composition and pH, well adapted microbial cultures were
established with high predictability with regard to these and other
parameters. This also helped in development of a stable balance of
buffers, minerals, cofactors and food that would produce manageable
amounts of gas given the constraints of high pressure on the
experimental reactors. Four different mother cultures of mixed
culture microorganisms were maintained over an extended period of
weeks. Data was collected over 3 months with good reproducibility
observed in the daily observations when the bioreactors were
centrifuged, off gassed, sampled, purged and replenished with fresh
media, and finally blanketed to be returned to the incubator. These
efforts helped design experiments that would be "substrate
limited." In other words, the batches would be limited only by the
presence of food, so that a maximum intrinsic growth rate could be
established based on the assumption that growth, particularly in
early log phase, would be dependent on food concentration and not
some other limiting nutrient or toxic byproduct of growth. Also,
care was taken to avoid substrate inhibition.
[0190] Monod Model describes this saturation kinetics, and works
well to model systems with slow growth and a low population
density. The Specific Growth rate is First order when the
concentration of food is low and then becomes Zero-order at large
concentrations of food.
.mu. growth = .mu. max s K S + S ; ##EQU00011##
where K.sub.S=Substrate concentration required to achieve 1/2
.mu..sub.max.
[0191] In any given batch, the initial food concentration is high
enough to attribute the observed maximum specific growth rate
entirely to the microorganism's intrinsic ability to replicate, or
double rapidly in a sustained fashion; just as one can determine a
rate of Yield of cell mass from a given amount of a particular
substrate for a specific organism (or for a well-trained and highly
adapted mixed culture).
[0192] Monod Model does not work well to describe very rapid dense
populations. Then interactions between species and product
inhibition can occur thereby reducing the specific growth rate
independent of the effect of substrate.
[0193] The Logistic Growth Model is consistent with the Monod Model
but takes into account the Lag Phase that always occurs upon
dilution of the starter cultures, or inoculums, and is better at
predicting the onset of the Declining Phase of a Bloom and
ultimately the Carrying Capacity of the batch. The basis of the
model is the following differential equation in which the rate of
change, or increase in a population, is directly related to the
population that is present at that time:
dP dt = rP ( 1 - P K ) ##EQU00012##
[0194] By rearrangement, one can see that the Specific Growth rate
is linearly related to P (the population present at any given
time); and that a plot of
( .DELTA. P P ) ##EQU00013##
vs F is linear and monotonically decreasing with a slope of (-r/K)
and a y-intercept of r:
.DELTA. P P = r - ( r K ) P ##EQU00014##
[0195] r represents the "boominess" of the system and K is the
Carrying Capacity of the system. Together these 2 parameters
describe the boom and bust of a batch growth reactor and the
maximum final population that can be achieved; which depends on the
substrate initially supplied and all other factors influencing
growth kinetics, especially the intrinsic growth rate of the
species present in the culture. So initial conditions matter
immensely in Batch experiments. The above equation can then be
integrated to give an analytical expression for the Population as a
function of time after r and K have been estimate from the linear
fit to the data:
P ( t ) = KP 0 P 0 + ( K - P 0 ) e - rt ##EQU00015##
where P.sub.0 is the population at time=0, and r is the growth rate
of cells.
[0196] This is the logistic equation for transient population
increase in a batch reactor. When the data can be fitted well to
this model, then population growth is typical of a batch bloom of
microorganisms, which display (1) lag phase, (2) exponential (log)
phase, (3) steady state or stationary phase, and (4) declining
phase.
[0197] Here, off-gassing, substrate uptake, and growth associated
product formation are studied as direct indicators of microbial
growth rates. In the mixed culture experiments, gas composition was
analyzed in order to determine the mass of CO.sub.2 and H.sub.2
that were released from each reactor. This release was attributed
entirely to either direct or indirect action of the microbes in log
growth on the batch reactor. Nitrogen was used to blanket each
reactor at every time stamp. Nitrogen production was on parity in
all cases. The surprising differences and effects of DryLet.RTM.
products are evidenced by log growth, which occurred sooner and
with much higher log rates of mass to gas than the control
situations.
[0198] Substrate uptake, when it is limited to only a few sugars,
was also used to track microbial growth, and displays predicted
logistic behavior. The experiments all focus on capturing data in
the early hours which correspond to log growth phases of each
culture and each reactor so that we can determine the effect on the
observed maximum growth rate when there is no endogenous decay,
when secondary blooms have not yet begun, and during which all
substrate uptake, gas production, and product formation are
directly associated with log growth of the population. The
DryLet.RTM. product produces a significantly higher intrinsic
growth rate as evidenced by the observable parameters.
[0199] In any bioprocess, just as in any typical chemical reactor,
a higher batch kinetic rate can always be applied to a continuous
process to achieve higher throughput, or an increased carrying
capacity of a chemostat to produce cell mass more rapidly per unit
time. By extension of these observations, the impact of pre-loading
and delivery of microorganisms in the form of DryLet.RTM. product
to any bioprocess chemostat (as in Example 1 at a full scale WWTP)
can be optimized to give higher yields of growth associated
products, more throughput in terms of the amount of substrate that
can be employed without causing substrate inhibition, the more BOD
and Chemical Oxygen Demand (COD) that can be consumed per unit
time, and an increased carrying capacity of the chemostat at
Steady-State.
[0200] The Malthusian Model of exponential growth in a batch system
(a.k.a. log growth) is given by the simple expression:
N(t)=N.sub.0e.sup.rt
[0201] in which N represents the number of cells and r is analogous
to the same term, which appears in the logistic curve fitting
equation. In a chemostat, r (the growth rate of cells) must exceed
the dilution rate, or washout occurs. If r>D, then an
equilibrium level of cell population, or the carrying capacity will
eventually be reached. This will depend on the intrinsic growth
rate of the microorganism (r), the Dilution rate (D), the cell mass
Yield (Y), and the Half-Concentration commonly denoted by
K.sub.S.
[0202] The "survival equilibrium" in a chemostat, or carrying
capacity is given by the following relationship:
N = S - K S D r - D Y ##EQU00016##
[0203] In contrast to batch, this survival equilibrium is
independent of the starting conditions. The experiments show that
one can achieve a lower K.sub.S and a higher r. These two
parameters in particular account for the increased carrying
capacity in Example 1.
[0204] Examples 1, 2, and 3 all show higher values for the observed
r in several different systems. Lower K.sub.S and higher value for
r both contribute to an elevated and accelerated population in a
chemostat when the DryLet.RTM. products are employed. The batch
results corroborate the increased carrying capacity that was
observed at full scale WWTP.
Example 2
[0205] Batch reactor vessels as shown in FIG. 15 were used to study
the carrying capacity of certain embodiments of the systems
disclosed herein. Typically, six to nine 1-liter Nalgene centrifuge
bottles were used as the fermentation vessels. Each vessel 1501 was
fitted with a rubber stopper 1502. A rubber septum 1503 over a
glass tube 1504 facilitated the extraction of gas and liquid
samples. The vessels have stainless steel rods 1505 that stir the
contents as the bottles are rotated in the incubator. Each vessel
was charged with roughly 250 ml of total broth, so that each bottle
contained 750 ml of headspace to accommodate the large amounts of
gas released from each system. The incubator was equipped with
rollers that rotate the vessels at 2 rpm. The temperature was held
at 40.degree. C. The fermentation vessels were loaded with the same
quantity of food source, nutrients, and inoculum. Two sets of three
vessels were used for the control and the experiment.
[0206] Substrates that are consumed anaerobically produce various
organic acids, which can lower the pH of the bioreaction. The pH
levels in the reactor were monitored and the acids produced are
readily consumed to form acetate and eventually methane and carbon
dioxide. The change in pH can be addressed by addition of external
acids or bases to maintain optimal conditions for the bioreaction.
Gas production volumes and composition of output gases from batch
reactors were analyzed, as well as substrate uptake rates and
volatile fatty acid production. Samples were extracted during each
of the experimental runs, which ranged from 18 to 30 hours in total
duration. Gas production, substrate uptake, and VFA production are
all correlated with microbial growth. Data was analyzed to
determine if preloaded immobilized delivery of an equal inoculum
into identical media with equal amounts of food would lead to log
growth phase more rapidly and at accelerated rates over control
situations.
[0207] Two types of growth media were used in the experiments. The
first growth medium selected for the methanogenic anaerobic
digestion contained only soluble components. The growth medium
consisted of a clarified fruit juice (apple juice was used here)
that contains nutrients (soluble sugars) and growth factors, such
as minerals and vitamins. To maintain near-neutral pH, the juice
was supplemented with calcium carbonate and phosphate buffer
similar to ATCC Medium 1398 (Modified low phosphate buffered basal
medium). The nitrogen source was yeast extract. De-oxygenated water
was prepared by boiling the contents pre-loaded with L-cysteine and
bisulfite, which also serve as oxygen scavengers. An example media
was prepared by adding 200 ml apple juice to 800 ml deoxygenated
water. About 5 grams yeast extract powder was added to that and
mixed. The pH of solution is then adjusted to 7.5 with the help of
10N sodium hydroxide. Both disodium hydrogen phosphate and
potassium dihydrogen phosphate are then added to the media that
acts as buffer. The prepared media was then autoclaved and
stored.
[0208] The second growth medium selected was based on the ATCC
formula for Reinforced Methanogens Growth Media. Two mineral
solutions--one containing 2.4 g of dibasic potassium phosphate in
400 ml deionized water and another containing 2.4 g each of
potassium dihydrogen phosphate and ammonium sulfate, 4.8 g of
sodium chloride and 0.6 g of calcium chloride in 400 ml of
deionized water--were mixed and diluted to one liter. The pH of the
solution was adjusted to 6.35 with the help of 300 .mu.L 10N sodium
hydroxide. Wolfe's vitamin solution and Wolfe's mineral solution
were added and the pH of the solution was adjusted to 7.35 with 100
.mu.L 10N NaOH and 1.5 g glycine. The final composition contained
about 60 ml of the mineral solution buffer, 8 ml of the yeast
solution, 2 ml of 88% formic acid, 5 g of sodium bicarbonate, and 8
ml of each of Wolfe's vitamin solution and Wolfe's mineral
solution.
[0209] Several distinct mother cultures, prepared and monitored as
shown in Table 24, were kept in daily fed batch stasis over a
period of 3 months. These mother cultures supplied the inoculums
for each experiment, while care was taken to cycle through the
stable mother cultures so that no two consecutive experiments
depleted the same mother culture.
TABLE-US-00026 TABLE 24 MOTHERS GBS Waco Digester 1 (D 1) Waco
Digester 2 (D 2) Food 5X dilution fruit juice Glucose, sucrose, 5X
dilution fruit juice (~22 g/l) total sugar liquid maltodextrin,
acid (~22 g/l) total sugar caseinate, ATCC P2 liquid media (~8 g/l
total) solids Growth Media #1 Filtered soluble fruit #2 ATCC Growth
#1 Filtered soluble juice with buffer, Media for methanogens, fruit
juice with buffer, minerals, growth factors, CaCO.sub.3, DryLet
.RTM. minerals, growth CaCO.sub.3 additives* factors, CaCO.sub.3
Sampling Daily (Gas volume, Gas Daily (Gas volume, Gas Daily (Gas
volume, Gas GC, weight) GC, weight) GC, weight) Daily Purge 100 ml
50 ml 80 ml Amount Avg. cc/day 900-1100 cc/day 1300-1700 cc/day
1000-1200 cc/day Avg. cc/hr ~40 cc/hr ~60 cc/hr ~45 cc/hr Avg. CO2%
50-30% 15-30% 15-30% Avg. N2% 60-80% 60-80% 60-80% Avg. CH4 0-10%
0-10% 0-10% Avg. H2% 5-20% 5-20% 5-20% Avg. pH 4.25-7.5 5.25-7.5
5.75-7.5 Note: pH was adjusted each day to 7.5.
[0210] The inoculum for each reactor was a 5 ml aliquot of a
homogenous broth, extracted via pipette after mixing the vessel of
the mother culture well; and each aliquot was supplied to one of
each of the reactors. In this way, each reactor received a nearly
an identical number of viable cells that were all exposed
instantaneously to a 50.times. dilution with regard to cell
concentration. This "shock" always resulted in a lag phase for
growth, which ranged from 4-6 hours.
[0211] The volume of gas produced in the vessels was measured by
displacing an aqueous solution of CaCl.sub.2 in a graduated water
column. In this instance, gas volumetric measurement was carried
out by calculating the volume of gas (cc) produced at each time
stamp along with the 750 ml headspace in each reactor and the 30 cc
sample removed for the gas chromatography. The composition of the
gas (methane, carbon dioxide, hydrogen, nitrogen) was measured by
gas chromatography. Sugar concentration from centrifuged 2 ml
samples was analyzed using a High Pressure Liquid Chromatography
(HPLC) system and UV detector. Gas-liquid chromatography was used
to measure acid production by concentration from centrifuged 2 ml
samples.
[0212] Three replicates for each of the two conditions--control and
treatment with silica microspheres loaded with
microorganisms--constituted six bottles under identical
experimental conditions and identical sampling regimens. Each of
these six bottles was filled with the same 250 mL of growth medium.
In each case, the total amount of broth used to inoculate each
bottle was 5 mL; however, under conditions using the precipitated
silica containing microorganisms, 5 ml of the culture broth was
mixed with an equal fraction of media, and then the resulting
solution was absorbed onto silica prior to being charged into the
reactor.
Example 2a
[0213] The growth kinetics of microorganisms growing under two
conditions were examined first, microorganisms that have been
introduced to the bioreactor as an inoculum from the mother
culture; and second, microorganisms that have been introduced to
the bioreactor as an inoculum from the mother culture along with
the addition of five grams of silica polymer to the bioreactor. The
energy solution consisted primarily of about six grams of glucose,
sucrose, and fructose. FIG. 16 is a graphical representation of the
growth kinetics of microorganisms growing under these conditions.
Both cultures entered log phase in about six hours. These sigmoidal
plots of population growth show the similarities in growth profiles
of the microorganisms under the two conditions.
[0214] In these experiments, the anaerobic bacteria converted the
nutrients m the growth medium into volatile acids and then into
biogas--a gas composed of methane and carbon dioxide, and trace
amounts of water vapor, hydrogen sulfide, and ammonia. FIG. 17 is a
graphical representation of the mass to gas percentage increase
(about 9% more) under the second growth conditions as compared to
that under the first growth conditions.
[0215] FIG. 18 is a graphical representation of the rate of sugar
consumption under the two growth conditions. There was a slightly
increased rate of consumption of sugars by bacteria growing in the
presence of the silica polymers added to the bioreactors. While the
sugar uptake reached completion around 18 hours under both
conditions, about 60% of the sugars were consumed by the
microorganisms in 9 hours growing in the presence of the silica
polymers added to the bioreactors versus the same 60% of the sugars
were consumed by the microorganisms in 11.5 hours growing under the
control conditions.
[0216] FIG. 19 is a graphical representation of the logarithmic
rate of sugar consumption under the two growth conditions. By 15
hours, nearly all of the sugar had been consumed in both reactors.
The rate of sugar consumption in the control reactor of 1.40 g/l/hr
and the microbes growing in the presence of the silica polymers had
a rate of sugar consumption of 1.46 g/l/hr. The control
underperformed by 4.3% relative to the silica reactor.
Example 2b
[0217] The growth kinetics of microorganisms growing under another
set of two conditions were examined-first, microorganisms that have
been introduced to the bioreactor as an inoculum from the mother
culture; and second, same amount of microorganisms that have been
loaded onto 6.5 grams of precipitated silica granules and then
introduced to the bioreactor. Compared to the previous sets of
growth conditions, the nutrient solution consisted primarily of
about four grams of glucose, sucrose, maltodextrin, and P2 media.
FIG. 20 is a graphical representation of the growth kinetics of
microorganisms growing these two conditions. The microorganisms
loaded onto precipitated silica granules entered log phase in about
five hours, while the microorganisms under the control conditions
entered log phase about two hours later.
[0218] FIG. 21 is a graphical representation of the mass to gas
percentage increase under the second growth conditions as compared
to that under the control growth conditions. There was a 54%
increase in the mass to gas percentage by the microorganisms loaded
onto precipitated silica granules under these growth conditions as
compared to the microorganisms under the control conditions. The
increased amount of gas (.about.1.6 times more) was being generated
at hour 12, indicating an increased microbial activity with
nutrients being converted to carbon dioxide and hydrogen. As this
was a batch reactor and the food was in fixed supply, the amount of
gas produced under the control conditions eventually caught up with
the amount of gas produced under conditions using the DryLet.RTM.
product. The rate of production of gases was accelerated by a
factor of 1.5. During the time period between 8 to 14 hours, the
relative rates of gas production were 0.075 g/hr and 0.05 g/hr by
the microorganisms loaded onto precipitated silica granules and by
the microorganisms under the control conditions respectively.
[0219] FIG. 22 is a graphical representation of the rate of sugar
consumption under the two growth conditions. About 60% of the
sugars were consumed by the microorganisms loaded onto precipitated
silica granules in 12 hours while a similar amount, 60% of the
sugars were consumed by the microorganisms in 18 hours growing
under the control conditions.
[0220] FIG. 23 is a graphical representation of the logarithmic
rate of sugar consumption under the two growth conditions. About
76.4% of the sugar was consumed by the microbes in the reactor
containing the DryLet.RTM. product 12 hours, while only 37.4% of
the sugar was consumed by the microbes in the control reactor at
the same time. The rate of sugar consumption in the reactor with
the DryLet.RTM. product was 0.382 g/l/hr and the rate of sugar
consumption in the control reactor was 0.187 g/l/hr. Thus, there
was 2.04 times more sugar consumption in the reactor containing the
DryLet.RTM. product as compared to the control reactor.
Example 2c
[0221] The growth kinetics of microorganisms growing under another
set of two conditions were examined-first, microorganisms that have
been introduced to the bioreactor as an inoculum from the mother
culture; and second, same amount of microorganisms that have been
loaded onto 6.5 grams of precipitated silica granules and then
introduced to the bioreactor. FIG. 24 is a graphical representation
of the growth kinetics of microorganisms growing under these two
conditions. Compared to the previous sets of growth conditions, the
energy solution consisted primarily of about six grams of glucose,
sucrose, and fructose. The microorganisms loaded onto precipitated
silica granules entered log phase in about five hours, while the
microorganisms under the control conditions entered log phase about
two hours later. The rate of gas production from hour 0 to hour 11
was at 0.16 g/hr and 0.11 g/hr for the reactors with DryLet.RTM.
product and the control respectively. Thus, there was a 43%
increase in the rate of gas production in the reactors with
DryLet.RTM. product.
[0222] FIG. 25 is a graphical representation of the mass to gas
percentage increase under the second growth conditions as compared
to that under the control growth conditions. The same trend as seen
in FIG. 27 was observed. The amount of gas produced at time zero
under both conditions was practically zero. The rate of increase
through the period 0 hours to 10 hours was about 0.08 g/hr and
0.055 g/hr when the microorganisms are loaded onto precipitated
silica granules and the microorganisms under the control conditions
respectively, thus, there was a 30% increase in the mass to gas
percentage by the microorganisms loaded onto precipitated silica
granules under these growth conditions as compared to the
microorganisms under the control conditions.
[0223] FIG. 26 is a graphical representation of the rate of sugar
consumption under the two growth conditions. About 60% of the
sugars were consumed by the microorganisms loaded onto precipitated
silica granules in 7 hours under these growth conditions while a
similar amount-60% of the sugars were consumed by the
microorganisms in 15 hours growing under the control conditions.
The rate of sugar consumption by the microorganisms loaded onto
precipitated silica granules, which was an indication of the
microbial population and carrying capacity, was shown to decrease
at a rate of 2.5 g/l/hr until the sugar concentration was too low
to sustain microbial growth. In same time period and through to 20
hours, the rate of sugar consumption by the microorganisms under
the control conditions was 1.1 g/l/hr. There was a 2.3 times
increase in rate of consumption of sugar by using DryLet.RTM.
product.
[0224] FIG. 27 is a graphical representation of the logarithmic
rate of sugar consumption under the two growth conditions.
[0225] FIG. 28 is a graphical representation of the mannitol
production under the two growth conditions. The initial rate of
mannitol production by the microorganisms loaded onto precipitated
silica granules under these growth conditions was 8 g/l/hr over the
period of 3.5 to 11 hours, whereas the rate of mannitol production
over the same time period under the control conditions was 0.28
g/l/hr. The concentration during the growth period reaches a much
higher concentration relative to the control indicating a much
higher carrying capacity when the microorganisms are loaded onto
precipitated silica granules. The amount of mannitol production
decreased with time after the peak because the feed sugar content
was depleted.
[0226] FIG. 29 is a graphical representation of the ethanol
production under the two growth conditions. Microorganisms loaded
onto precipitated silica granules under these growth conditions
showed a higher rate, faster time to ethanol production, along with
an increase in carrying capacity for ethanol generation. The rate
of production of ethanol was accelerated during the 3-hour to
8-hour time period, when the system reaches the stationary phase.
The rate of ethanol production by microorganisms loaded onto
precipitated silica granules was 0.3 g/l/hr, whereas the control
has zero ethanol production in this period. Its production of
ethanol was retarded by 4 hours under the control conditions and
the growth rate through to 10 hours was 0.08 g/l/hr. The rate of
ethanol production by microorganisms loaded onto precipitated
silica granules was about 3.7 times faster than the control. As
these are operated under batch reactor conditions with only limited
amount of food, the rates reach a stationary phase and increasing
concentration of the alcohol can slow the rate of production once a
significant concentration has been reached. Thus, the carrying
capacity of the system was increased when the microorganisms were
loaded onto precipitated silica granules before being introduced to
the bioreaction.
[0227] FIG. 30 is a graphical representation of the sugar uptake
under the two growth conditions. The rate of sugar consumption by
microorganisms loaded onto precipitated silica granules and by
microorganisms under control conditions from time zero to 10 hours
were approximately 2.4 g/l/hr and 1.1 g/l/hr, respectively. Thus,
the carrying capacity of the system was increased at least by 2.2
fold when the microorganisms are loaded onto precipitated silica
granules before being introduced to the bioreaction.
Example 2d
[0228] The growth kinetics of microorganisms growing under two
conditions were examined--first, microorganisms that have been
introduced to the bioreactor as an inoculum from the mother
culture; and second, same amount of microorganisms that have been
loaded onto 6.5 grams of precipitated silica granules and then
introduced to the bioreactor. FIG. 31 is a graphical representation
of the growth kinetics of microorganisms growing under these two
conditions. Compared to the previous sets of growth conditions, the
energy solution here consisted primarily of about four grams of
glucose, sucrose, maltodextrin, and P2 media. The microorganisms
loaded onto precipitated silica granules entered log phase in about
five hours, while the microorganisms under the control conditions
entered log phase about two hours later.
[0229] FIG. 32 is a graphical representation of the mass to gas
percentage increase under the second growth conditions as compared
to that under the control growth conditions. There was a 47%
increase in the mass to gas percentage by the microorganisms loaded
onto precipitated silica granules under these growth conditions as
compared to the microorganisms under the control conditions.
[0230] FIG. 33 is a graphical representation of the rate of sugar
consumption under the two growth conditions. About 60% of the
sugars were consumed by the microorganisms loaded onto precipitated
silica granules in 10 hours under these growth conditions while a
similar amount (60%) of the sugars were consumed by the
microorganisms in 11.5 hours growing under the control
conditions.
[0231] FIG. 34 is a graphical representation of the logarithmic
rate of sugar uptake under the two growth conditions.
[0232] FIG. 35 is a diagrammatic representation of the experimental
set-up designed to study the amount of gasses produced by the
anaerobic systems. Each bioreactor 3501 was fitted with a
tightfitting stopper and an exit tube 3502. The exit tube 3502 was
connected to an inverted graduated cylinder 3503, placed in another
vessel 3504 containing about 300 g/L of CaCb. In this instance, gas
volumetric measurement was carried out by measuring the volume of
liquid (cc) displaced by the gas produced with time along with the
headspace in each reactor 3501. A 30 cc sample was removed for
analysis by gas chromatography in the total amount of gas produced.
Samples were analyzed according to previously described
methods.
[0233] FIG. 36 is a graphical representation of the average mass
rate of gasses produced under the two growth conditions described
in Example 2a.
[0234] FIG. 37 is a graphical representation of the average mass
rate of gasses produced under the two growth conditions described
in Example 2b. The graphs show that a constant amount of gas was
produced by the mother culture, while there was an increased rate
of gas produced by the microorganisms that are loaded onto
precipitated silica granules (DryLet.RTM. product) before being
introduced to the bioreaction relative to the control samples.
[0235] FIG. 38 is a graphical representation of the average mass
rate of gasses produced under the two growth conditions described
in Example 2c. The graphs show that a constant amount of gas was
produced by the mother culture, while there was an increased rate
of gas produced by the microorganisms that are loaded onto
precipitated silica granules (DryLet.RTM. product) before being
introduced to the bioreaction relative to the control samples.
[0236] FIG. 39 is a graphical representation of the average mass
rate of gasses produced under the two growth conditions described
in Example 2d. The graphs show that a constant amount of gas was
produced by the mother culture, while there was an increased rate
of gas produced by the microorganisms that are loaded onto
precipitated silica granules (DryLet.RTM. product) before being
introduced to the bioreaction relative to the control samples. The
initial low value for gas evolution was because of the test dilutes
the amount of culture initially. There was rapid gas increase
followed by reaching a peak of gas evolution for both DryLet.RTM.
product and control followed by decay as the microbes reach the
stationary phase.
[0237] Summary of the results from Examples 2a-2d are presented in
Table 25.
TABLE-US-00027 TABLE 25 Mass to Mass to gas % gas % increase
increase Time Time to over over to Time to reach Mother Controls
reach consume 60% max max log 60% of Carrying pH Mother Food
(cc/hr) (cc/hr) phase sugars Capacity range Example 2a GBS Glucose,
250% 40% 6 hrs 9 hrs 14.5 hrs 4.25-7.5 3 Controls sucrose, for vs
for both and 3 fructose both 11.5 hrs reactors with (~6 grams)
independent 2.4% addition of wt./vol. silica and microbes Example
2b D1 Sucrose, 200% 62% 5 hrs 12 hrs 12 hrs 5-7.5 3 Controls
glucose, vs vs vs and 3 maltodextrin, 7 hrs 18 hrs 14.5 hrs
reactors with P2 DryLet .RTM. media product (~4 grams) 1.6%
wt./vol. Example 2c D2 Glucose, 367% 210% 5 hrs 7 hrs 8.5 hrs
5.75-7.5 3 Controls sucrose, vs vs vs and 3 fructose 7 hrs 15 hrs
10.5 hrs reactors with (~6 grams) DryLet .RTM. 2.4% product
wt./vol. Example 2d D1 Sucrose, 175% 36% 5 hrs 10 hrs 10 hrs
5.25-7.5 3 Controls glucose, vs vs vs and 3 maltodextrin, 7 hrs
11.5 hrs 11.5 hrs reactors with P2 DryLet .RTM. media product (~4
grams) 2.4% wt./vol.
[0238] Other embodiments include a method of increasing the
capacity for digestion in an anaerobic or anoxic process, as are
commonly encountered in the wastewater industry in the form of
anaerobic digesters and anoxic bioreactors (or anoxic "zones"). The
microbial cultures used in Examples 2b, 2c, and 2d were all
obtained directly from an anaerobic methane producing digester. The
results show that digestion and gas production from such digesters
can be greatly increased just as in the aerobic case in Example 1.
CO.sub.2 and H.sub.2 gas formation are precursors to methane
formation. By accelerating the rate and the amounts of CO.sub.2 and
H.sub.2 in a bioreactor that is strictly anaerobic will lead to
increased methane formation and more complete digestion of biomass
contained in an anaerobic digester. Similarly, an anoxic bioreactor
can also be accelerated by DryLet.RTM. product to accomplish
denitrification at an accelerated catalyzed rate. All three
conditions exist in wastewater lagoons, wherein the water near the
surface may be well oxygenated, the solids blanket at the bottom of
a lagoon will certainly be anaerobic (unless air is applied), and
the water in between would be characterized as anoxic with regard
to its dissolved oxygen levels.
Example 3
[0239] Experiments were conducted to examine how growth patterns of
a single microbial species can be altered by changing the amount of
silica polymers, the mode of application of the microbes and the
silica polymers, and the amount of nutrients in the system. For
these experiments, the starting culture was Clostridium
acetobutylicum ATCC 39236 initial prepared as instructed by ATCC. A
batch of P2 media (Difco.TM. Reinforced Clostridial Medium) was
inoculated from the mother culture. Over a period of -36 hours,
samples were taken frequently (.about.1.5 hours) and analyzed for
the consumption of sugars and production of gaseous and liquid
products. These data were analyzed to determine the growth rate of
cells without DryLet.RTM. product (control) and with DryLet.RTM.
product. The fermentation was performed in modified 1-L propylene
centrifuge bottles sold by Beckman. These 1-L centrifuge bottles
were placed horizontally in a Wheaton.RTM. modular cell culture
roller bottle apparatus with multiple decks of parallel rollers
that rotated the bottles at approximately 2.0 rpm. The incubator
was a custom-made cabinet that contains the roller apparatus. The
dimensions are similar to a home-refrigerator. The incubator
circulates air through a bank of heaters to regulate the
temperature to 40.degree. C. Measurements of gas production were
carried out as previously described above. Liquids were analyzed by
gas chromatography. Acids were analyzed according to the methods
employed by Earth Energy Renewables. The samples were filtered to
remove debris. Phosphoric acid was added to acidify the solution so
all acids are volatile. An internal standard was added for
calibration purposes. A set of bioreactors were setup under
conditions described in Table 26. As used in reactors described in
Tables 26 and 27, the term "Low Silica" refers to reactor
conditions, where 15 g of precipitated silica granules were added
independently of the microbes to the reactor. The term "High
Silica" refers to reactor conditions, where 30 g of precipitated
silica granules were added independently of the microbes to the
reactor. The term "Low DryLet.RTM. Product" refers to reactor
conditions, where 15 g of precipitated silica granules were loaded
with 15 mL of the microbial culture before addition to the reactor.
The term "High DryLet.RTM. Product" refers to reactor conditions,
where 30 g of precipitated silica granules were loaded with 30 mL
of the microbial culture before addition to the reactor.
TABLE-US-00028 TABLE 26 Reactor No. 4 3 Low Food 1 2 Low Food High
5 Low Food Low Food Low DryLet .RTM. DryLet .RTM. Low Food
Conditions Low Silica High Silica Product Product Control Food 15
g/L 15 g/L 15 g/L 15 g/L 15 g/L (concentration of D-Mannose in
reactor) Amount of 30 mL 30 mL 15 mL 30 mL 30 mL Starter culture
Amount of 15 g 30 g 15 g 30 g 0 g silica Mode of Microbes and
Microbes and Microbes Microbes Only delivery precipitated
precipitated loaded onto loaded onto Microbes silica granules
silica granules precipitated precipitated added added silica
granules silica granules independently independently before before
to reactor to reactor addition to addition to reactor reactor
[0240] The metabolic kinetics of microorganisms growing under three
conditions (Reactors 1, 3, and 5 in Table 26) were examined. FIG.
40 is a graphical representation of the total gas produced per unit
vol. of starting culture when there was lower amount food in the
system (15 g/l). About 15 mL of the starter culture was loaded onto
silica granules (DryLet.RTM. product) before supplying them to
Reactor 3, whereas 30 mL was loaded along with the 15 g of silica
into Reactor 1. Using the DryLet.RTM. product led to almost 200%
more gas per unit volume of starting culture in Reactor 3 as
compared to the amount of gas produced in Reactor 1 and 5. FIG. 41
is a graphical representation of the rate of gas (cc/hr) generated
under three conditions (Reactors 1, 3, and 5) normalized to the
amount of unit volume in the starting culture as measured by
milliliters (ml). Using the DryLet.RTM. product led to a gas
production rate that was 2.24 times greater than the gas production
rate in Reactor 1 and 5.
[0241] FIG. 42 is a graphical representation of butyric acid
production per unit volume of starting culture when there was lower
amount food in the system (15 g/l). Using the DryLet.RTM. product
generated 2.02 times more butyric acid (mg/ml) than the acid
produced in Reactor 1 from time 22 hrs until reaction completion at
time 72 hours. FIG. 43 is a graphical representation of the rate of
butyric acid production per unit volume of starting culture when
there was lower amount food in the system (15 g/l). Using the Dry
Let.RTM. product, the rate of butyric acid production was 2.41
times greater than the acid production rate in Reactor 1 from time
22 hrs until reaction completion at time 72 hours.
[0242] The metabolic kinetics of microorganisms growing under three
conditions (Reactors 2, 4, and 5 in Table 26) were examined. FIG.
44 is a graphical representation of the total gas produced per unit
vol. of starting culture when there was lower amount food in the
system (15 g/l) but the amount of silica present was increased to
30 g. Using the DryLet.RTM. product led to almost 46% more gas per
unit volume of starting culture in Reactor 4 as compared to the
amount of gas produced in Reactor 2 and 5. Even during stationary
phase, using the DryLet.RTM. product produced a steady rate of 20%
to 30% more gas as compared to the amount of gas produced in
Reactor 2 until the food was exhausted. FIG. 45 is a graphical
representation of the rate of gas (cc/hr) generated under three
conditions (Reactors 2, 4, and 5 in Table 26) normalized to the
amount of unit volume in the starting culture as measured by
milliliters (ml). Using the DryLet.RTM. product led to a gas
production rate that was 1.58 times greater than the gas production
rate in Reactor 2 and 5. There was also an earlier peak in
production in Reactor 4. Using the DryLet.RTM. product led to a gas
production rate of 4.56 cc/hr/ml at approximately 22 hrs, as
compared to a gas production rate of 2.88 cc/hr/ml at approximately
30 hrs. This shows that the metabolic process for conversion of the
food started about 8 hours earlier in Reactor 4 than in Reactor 2
and the peak gas rate was 58.3% greater in Reactor 4.
[0243] FIG. 46 is a graphical representation of butyric acid
production per unit volume of starting culture when there was lower
amount food in the system (15 g/l) but the amount of silica present
was increased to 30 g. In Reactor 4, butyric acid production
started 4 hours earlier (time=14 hours) as compared to the butyric
acid production in Reactor 2. And, there was higher butyric acid
production per unit volume of starting culture (mg/ml)--34.92 mg/ml
in Reactor 4 as compared to the 31.27 mg/ml in Reactor 2; an 11.7%
increase in butyric acid production.
[0244] FIG. 47 is a graphical representation of the rate of butyric
acid production per unit volume of starting culture when there was
lower amount food in the system (15 g/l) but the amount of silica
present was increased to 30 g. Using the DryLet.RTM. product, the
rate of butyric acid production was about 1.77 to 2.23 mg/hr/ml and
was sustained for 12 hours in Reactor 5. Although the use of
microbes and silica independently in Reactor 2 also led to a
similar peak rate of butyric acid production of 2.22 mg/hr/ml, this
rate was reached about four hours later and lasted only about an
hour.
[0245] A set of bioreactors were setup under conditions described
in Table 27.
TABLE-US-00029 TABLE 27 Reactor No. 9 8 High Food 6 7 High Food
High 10 High Food High Food Low DryLet .RTM. DryLet .RTM. High Food
Conditions Low Silica High Silica Product Product Control Food 30
g/L 30 g/L 30 g/L 30 g/L 30 g/L (concentration of D-Mannose in
reactor) Amount of 30 mL 30 mL 15 mL 30 mL 30 mL Starter culture
Amount of 15 g 30 g 15 g 30 g 0 g silica Mode of Microbes and
Microbes and Microbes Microbes Only delivery precipitated
precipitated loaded onto loaded onto Microbes silica granules
silica granules precipitated precipitated added added silica
granules silica granules independently independently before before
to reactor to reactor addition to addition to reactor reactor
[0246] The metabolic kinetics of microorganisms growing under three
conditions (Reactors 6, 8, and 10 in Table 27) were examined. FIG.
48 is a graphical representation of the total gas produced per unit
vol. of starting culture when there was larger amount food in the
system (30 g/l). About 15 mL of the starter culture was loaded onto
silica granules (DryLet.RTM. product) before supplying them to
Reactor 8, whereas 30 mL was loaded along with the 15 g of silica
into Reactor 6. From initial gas production at time=8 hours for all
reactors, more gas (cc) per unit volume of starting culture (ml)
was produced in Reactor 8 as compared to Reactors 6 and 10. Using
the DryLet.RTM. product led to almost 117% more gas per unit volume
of starting culture in Reactor 8 as compared to the amount of gas
produced in Reactor 6 and 10.
[0247] FIG. 49 is a graphical representation of the rate of gas
(cc/hr) generated under three conditions (Reactors 6, 8, and 10 in
Table 27) normalized to the amount of unit volume in the starting
culture as measured by milliliters (ml). Using the DryLet.RTM.
product led to a gas production rate that was 2.33 times greater
than the gas production rate in Reactor 6. In Reactor 8, the peak
gas production rate was 3.55 cc/hr/ml (at time=38 hrs), whereas in
Reactor 6, the peak gas production rate was 1.52 cc/hr/ml (time=38
hrs). Moreover, the metabolic process for significant conversion of
the food started earlier in Reactor 8 at t=18 hours than in Reactor
6 at t=38 hours. Reactor 8 had a maximum rate of gas production
that was almost 2.34 times greater than the gas production rate in
Reactor 6.
[0248] FIG. 50 is a graphical representation of butyric acid
production per unit volume of starting culture when there was
larger amount food in the system (30 g/l). Butyric acid production
was negligible in Reactors 6 and 10. Only Reactor 8 produced
butyric acid of about 29.66 mg/ml. FIG. 51 is a graphical
representation of the rate of butyric acid production per unit
volume of starting culture. The maximum rate was 1.19 mg/hr/ml in
Reactor 8, while the rates were negligible in Reactors 6 and 10 due
to lack of butyric acid production.
[0249] The metabolic kinetics of microorganisms growing under three
conditions (Reactors 7, 9, and 10) were examined. FIG. 52 is a
graphical representation of the total gas produced per unit vol. of
starting culture when there was larger amount food in the system
(30 g/l) and the amount of silica present was increased to 30 g.
Use of the DryLet.RTM. product led to almost 144% more gas per unit
volume of starting culture in Reactor 9 as compared to the amount
of gas produced in Reactors 7 and 10. Use of the DryLet.RTM.
product exhibited a significant increase in total gas produced per
unit volume of starting culture (ml) at time=30 hours and was
maintained until completion at time=72 hours.
[0250] FIG. 53 is a graphical representation of the rate of gas
(cc/hr) generated under three conditions (Reactors 7, 9, and 10 in
Table 27) normalized to the amount of unit volume in the starting
culture as measured by milliliters (ml). Using the DryLet.RTM.
product led to a gas production rate that was 3.05 times greater
than the gas production rate in Reactor 7 and 10. There was also an
earlier peak in production in Reactor 9. Using the DryLet.RTM.
product led to a gas production rate of 4.64 cc/hr/ml at
approximately 30 hrs, as compared to a gas production rate of 1.52
cc/hr/ml at approximately 38 hrs. This shows that the metabolic
process for conversion of the food started about 8 hours earlier in
Reactor 9.
[0251] FIG. 54 is a graphical representation of butyric acid
production per unit volume of starting culture when there was
larger amount food in the system (30 g/l) and the amount of silica
present was increased to 30 g. Butyric acid production was
negligible in Reactors 7 and 10. Only Reactor 9 produced butyric
acid at time=36 hours to 72 hours in a range of 22.7 to 27.22
mg/ml. FIG. 55 is a graphical representation of the rate of butyric
acid production per unit volume of starting culture. The maximum
rate was 1.95-2.27 mg/hr/ml in Reactor 9, while the rates were
negligible in Reactors 7 and 10 due to lack of butyric acid
production.
[0252] This Example demonstrates that the addition of silica
polymers to a bioreactor containing microbes increases microbial
growth and several metabolic processes as compared to a control
bioreactor without the silica polymers. The use of DryLet.RTM.
product dramatically increased microbial growth and the rate of
production of products by the microbes as compared to the control
bioreactors.
[0253] As used herein, "about" refers to a degree of deviation
based on experimental error typical for the particular property
identified. The latitude provided the term "about" will depend on
the specific context and particular property and can be readily
discerned by those skilled in the art. The term "about" is not
intended to either expand or limit the degree of equivalents which
may otherwise be afforded a particular value. Further, unless
otherwise stated, the term "about" shall expressly include
"exactly," consistent with the discussion below regarding ranges
and numerical data.
[0254] Concentrations, amounts, and other numerical data may be
expressed or presented herein in a range format. It is to be
understood that such a range format is used merely for convenience
and brevity and thus should be interpreted flexibly to include not
only the numerical values explicitly recited as the limits of the
range, but also to include all the individual numerical values or
sub-ranges encompassed within that range as if each numerical value
and sub-range is explicitly recited. As an illustration, a
numerical range of "about 1 to about 5" should be interpreted to
include not only the explicitly recited values of about 1 to about
5, but also include individual values and sub-ranges within the
indicated range. Thus, included in this numerical range are
individual values such as 2, 3.5, and 4 and sub-ranges such as from
1-3, from 2-4, and from 3-5, etc. Additionally, a numerical range
with a lower end of "0" can include a sub-range using "0.1" as the
lower end point.
[0255] While the disclosure has been described with reference to
certain examples, those skilled in the art will appreciate that
various modifications, changes, omissions, and substitutions can be
made without departing from the spirit of the disclosure. It is
intended, therefore, that the present disclosure be limited only by
the scope of the following claims.
* * * * *
References